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Last updated on 2026-07-16 06:53:34 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0.3 | 80.62 | 266.82 | 347.44 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.0.3 | 55.71 | 129.98 | 185.69 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.0.3 | 115.00 | 326.37 | 441.37 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 1.0.3 | 64.00 | 153.57 | 217.57 | ERROR | |
| r-devel-windows-x86_64 | 1.0.3 | 92.00 | 190.00 | 282.00 | ERROR | |
| r-patched-linux-x86_64 | 1.0.3 | 70.86 | 229.15 | 300.01 | ERROR | |
| r-release-linux-x86_64 | 1.0.3 | 76.95 | 235.87 | 312.82 | ERROR | |
| r-release-macos-arm64 | 1.0.3 | 16.00 | 70.00 | 86.00 | OK | |
| r-release-macos-x86_64 | 1.0.3 | 50.00 | 304.00 | 354.00 | OK | |
| r-release-windows-x86_64 | 1.0.3 | 93.00 | 177.00 | 270.00 | ERROR | |
| r-oldrel-macos-arm64 | 1.0.3 | 14.00 | 65.00 | 79.00 | OK | |
| r-oldrel-macos-x86_64 | 1.0.3 | 61.00 | 355.00 | 416.00 | OK | |
| r-oldrel-windows-x86_64 | 1.0.3 | 113.00 | 228.00 | 341.00 | ERROR |
Version: 1.0.3
Check: examples
Result: ERROR
Running examples in ‘pprof-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: SM_output.logis_re
> ### Title: Calculate direct/indirect standardized ratios/rates from a
> ### fitted 'logis_re' object
> ### Aliases: SM_output.logis_re
>
> ### ** Examples
>
> data(ExampleDataBinary)
> outcome = ExampleDataBinary$Y
> covar = ExampleDataBinary$Z
> ProvID = ExampleDataBinary$ProvID
> fit_re <- logis_re(Y = outcome, Z = covar, ProvID = ProvID)
Input format: Y, Z, and ProvID.
Error: Downdated VtV is not positive definite
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
SM_output.logis_cre 14.262 0.071 17.095
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.0.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [89s/114s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-SM_output-99.R
Saving _problems/test-SM_output-125.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
OMP: Warning #96: Cannot form a team with 4 threads, using 3 instead.
OMP: Hint Consider unsetting KMP_DEVICE_THREAD_LIMIT (KMP_ALL_THREADS), KMP_TEAMS_THREAD_LIMIT, and OMP_THREAD_LIMIT (if any are set).
Saving _problems/test-confint-165.R
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: data, Y.char, Z.char, and ProvID.char.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: formula and data.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-summary-90.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-test-106.R
Saving _problems/test-test-129.R
[ FAIL 6 | WARN 0 | SKIP 0 | PASS 141 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-SM_output.R:99:3'): SM_output.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-SM_output.R:99:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-SM_output.R:125:3'): SM_output.logis_cre function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-SM_output.R:125:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-confint.R:165:3'): test.logis_cre function behaves correctly ───
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-confint.R:165:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-summary.R:90:3'): summary.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-summary.R:90:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:106:3'): test.logis_re function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-test.R:106:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:129:3'): test.logis_cre function behaves correctly ──────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-test.R:129:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
[ FAIL 6 | WARN 0 | SKIP 0 | PASS 141 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.0.3
Check: examples
Result: ERROR
Running examples in ‘pprof-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: SM_output.logis_cre
> ### Title: Calculate direct/indirect standardized ratios/rates from a
> ### fitted 'logis_cre' object
> ### Aliases: SM_output.logis_cre
>
> ### ** Examples
>
> data(ExampleDataBinary)
> outcome <- ExampleDataBinary$Y
> covar <- ExampleDataBinary$Z
> ProvID <- ExampleDataBinary$ProvID
> data <- data.frame(outcome, ProvID, covar)
> outcome.char <- colnames(data)[1]
> ProvID.char <- colnames(data)[2]
> wb.char <- c("z1", "z2")
> other.char <- c("z3", "z4", "z5")
> fit_cre <- logis_cre(data = data, Y.char = outcome.char, ProvID.char = ProvID.char,
+ wb.char = wb.char, other.char = other.char)
Error: Downdated VtV is not positive definite
Execution halted
Flavors: r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64
Version: 1.0.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [21s/25s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-SM_output-99.R
Saving _problems/test-SM_output-125.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-confint-132.R
Saving _problems/test-confint-165.R
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Saving _problems/test-logis_cre-13.R
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: data, Y.char, Z.char, and ProvID.char.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: formula and data.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
*** caught segfault ***
address 0x5640417be830, cause 'memory not mapped'
Traceback:
1: pwrssUpdate(pp, resp, tol = tolPwrss, GQmat = GQmat, compDev = compDev, grpFac = fac, maxit = maxit, verbose = verbose)
2: fn(nM$xeval())
3: stopifnot(length(value <- as.numeric(value)) == 1L)
4: nM$newf(fn(nM$xeval()))
5: (function (fn, par, lower = rep.int(-Inf, n), upper = rep.int(Inf, n), control = list()) { n <- length(par) if (is.null(xst <- control[["xst"]])) xst <- rep.int(0.02, n) if (is.null(xt <- control[["xt"]])) xt <- xst * 5e-04 control[["xst"]] <- control[["xt"]] <- NULL if (is.null(verbose <- control[["verbose"]])) verbose <- 0 control[["verbose"]] <- NULL if (is.null(control[["iprint"]])) { control[["iprint"]] <- switch(as.character(min(as.numeric(verbose), 3L)), `0` = 0, `1` = 20, `2` = 10, `3` = 1) } stopifnot(is.function(fn), length(formals(fn)) == 1L, (n <- length(par <- as.numeric(par))) == length(lower <- as.numeric(lower)), length(upper <- as.numeric(upper)) == n, length(xst <- as.numeric(xst)) == n, all(xst != 0), length(xt <- as.numeric(xt)) == n) nM <- NelderMead$new(lower = lower, upper = upper, x0 = par, xst = xst, xt = xt) cc <- do.call(function(iprint = 0L, maxfun = 10000L, FtolAbs = 1e-05, FtolRel = 1e-15, XtolRel = 1e-07, MinfMax = -.Machine$double.xmax, warnOnly = FALSE, ...) { if (...length() > 0) warning("unused control arguments ignored") list(iprint = iprint, maxfun = maxfun, FtolAbs = FtolAbs, FtolRel = FtolRel, XtolRel = XtolRel, MinfMax = MinfMax, warnOnly = warnOnly) }, control) nM$setFtolAbs(cc$FtolAbs) nM$setFtolRel(cc$FtolRel) nM$setIprint(cc$iprint) nM$setMaxeval(cc$maxfun) nM$setMinfMax(cc$MinfMax) it <- 0 repeat { it <- it + 1 nMres <- nM$newf(fn(nM$xeval())) if (nMres != 0L) break } cmsg <- "reached max evaluations" if (nMres == -4) { cmsg <- warning(sprintf("failure to converge in %d evaluations", cc$maxfun)) nMres <- 4 } msgvec <- c("nm_forced", "cannot generate a feasible simplex", "initial x is not feasible", "active", "objective function went below allowed minimum", "objective function values converged to within tolerance", "parameter values converged to within tolerance", cmsg) if (nMres < 0) { (if (cc$warnOnly) warning else stop)(msgvec[nMres + 4]) } list(fval = nM$value(), par = nM$xpos(), convergence = pmin(0, nMres), NM.result = nMres, message = msgvec[nMres + 4], control = c(cc, xst = xst, xt = xt), feval = it)})(fn = function (pars) { resp$setOffset(baseOffset) resp$updateMu(lp0) pp$setTheta(mkTheta(as.double(pars[dpars]))) spars <- as.double(pars[-dpars]) offset <- if (length(spars) == 0) baseOffset else baseOffset + pp$X %*% spars resp$setOffset(offset) p <- pwrssUpdate(pp, resp, tol = tolPwrss, GQmat = GQmat, compDev = compDev, grpFac = fac, maxit = maxit, verbose = verbose) resp$updateWts() p}, par = c(0.468607523292137, -0.972251105312955, 1.07368783024528, 1.00545583069717, 0.982297419628586, 1.02159424566637, 1.03318616583394), lower = c(0, -Inf, -Inf, -Inf, -Inf, -Inf, -Inf), upper = c(Inf, Inf, Inf, Inf, Inf, Inf, Inf), control = list(xst = c(0.02, 0.0120964948228697, 0.00806677239991467, 0.00801317258186648, 0.00783753005989266, 0.00800874015940586, 0.00811250580290572), xt = c(1e-05, 6.04824741143487e-06, 4.03338619995733e-06, 4.00658629093324e-06, 3.91876502994633e-06, 4.00437007970293e-06, 4.05625290145286e-06), verbose = 0L))
6: do.call(optfun, arglist)
7: withCallingHandlers(do.call(optfun, arglist), warning = function(w) { curWarnings <<- append(curWarnings, list(w$message))})
8: optwrap(optimizer, devfun, start, lower = lower, upper = upper, control = control, adj = nAGQ > 0L, verbose = verbose, ...)
9: optimizeGlmer(devfun, optimizer = control$optimizer[[2]], restart_edge = control$restart_edge, boundary.tol = control$boundary.tol, control = control$optCtrl, start = start, nAGQ = nAGQ, verbose = verbose, calc.derivs = calc.derivs, use.last.params = control$use.last.params)
10: glmer(formula, data, family = binomial(link = "logit"), ...)
11: logis_re(Y = Y, Z = Z, ProvID = ProvID)
12: eval(code, test_env)
13: eval(code, test_env)
14: withCallingHandlers({ eval(code, test_env) new_expectations <- the$test_expectations > starting_expectations if (snapshot_skipped) { skip("On CRAN") } else if (!new_expectations && skip_on_empty) { skip_empty() }}, expectation = handle_expectation, packageNotFoundError = function(e) { if (on_cran()) { skip(paste0("{", e$package, "} is not installed.")) }}, snapshot_on_cran = function(cnd) { snapshot_skipped <<- TRUE invokeRestart("muffle_cran_snapshot")}, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error, interrupt = handle_interrupt)
15: doTryCatch(return(expr), name, parentenv, handler)
16: tryCatchOne(expr, names, parentenv, handlers[[1L]])
17: tryCatchList(expr, classes, parentenv, handlers)
18: tryCatch(withCallingHandlers({ eval(code, test_env) new_expectations <- the$test_expectations > starting_expectations if (snapshot_skipped) { skip("On CRAN") } else if (!new_expectations && skip_on_empty) { skip_empty() }}, expectation = handle_expectation, packageNotFoundError = function(e) { if (on_cran()) { skip(paste0("{", e$package, "} is not installed.")) }}, snapshot_on_cran = function(cnd) { snapshot_skipped <<- TRUE invokeRestart("muffle_cran_snapshot")}, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error, interrupt = handle_interrupt), error = handle_fatal)
19: doWithOneRestart(return(expr), restart)
20: withOneRestart(expr, restarts[[1L]])
21: withRestarts(tryCatch(withCallingHandlers({ eval(code, test_env) new_expectations <- the$test_expectations > starting_expectations if (snapshot_skipped) { skip("On CRAN") } else if (!new_expectations && skip_on_empty) { skip_empty() }}, expectation = handle_expectation, packageNotFoundError = function(e) { if (on_cran()) { skip(paste0("{", e$package, "} is not installed.")) }}, snapshot_on_cran = function(cnd) { snapshot_skipped <<- TRUE invokeRestart("muffle_cran_snapshot")}, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error, interrupt = handle_interrupt), error = handle_fatal), end_test = function() { })
22: test_code(code, parent.frame())
23: test_that("logis_re function behaves correctly", { data(ExampleDataBinary) Y <- ExampleDataBinary$Y Z <- ExampleDataBinary$Z ProvID <- ExampleDataBinary$ProvID data <- data.frame(Y, ProvID, Z) Z.char <- colnames(Z) Y.char <- "Y" ProvID.char <- "ProvID" formula <- as.formula(paste("Y ~", paste(Z.char, collapse = " + "), "+ (1 | ProvID)")) fit_re1 <- logis_re(Y = Y, Z = Z, ProvID = ProvID) fit_re2 <- logis_re(data = data, Y.char = Y.char, Z.char = Z.char, ProvID.char = ProvID.char) fit_re3 <- logis_re(formula, data) expect_true(all(class(fit_re1) == "logis_re", class(fit_re2) == "logis_re", class(fit_re3) == "logis_re"), info = "All models should be of class 'logis_re'.") expect_true(all(all.equal(fit_re1$fitted, fit_re2$fitted), all.equal(fit_re1$fitted, fit_re3$fitted)), info = "All models have the same result.")})
24: eval(code, test_env)
25: eval(code, test_env)
26: withCallingHandlers({ eval(code, test_env) new_expectations <- the$test_expectations > starting_expectations if (snapshot_skipped) { skip("On CRAN") } else if (!new_expectations && skip_on_empty) { skip_empty() }}, expectation = handle_expectation, packageNotFoundError = function(e) { if (on_cran()) { skip(paste0("{", e$package, "} is not installed.")) }}, snapshot_on_cran = function(cnd) { snapshot_skipped <<- TRUE invokeRestart("muffle_cran_snapshot")}, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error, interrupt = handle_interrupt)
27: doTryCatch(return(expr), name, parentenv, handler)
28: tryCatchOne(expr, names, parentenv, handlers[[1L]])
29: tryCatchList(expr, classes, parentenv, handlers)
30: tryCatch(withCallingHandlers({ eval(code, test_env) new_expectations <- the$test_expectations > starting_expectations if (snapshot_skipped) { skip("On CRAN") } else if (!new_expectations && skip_on_empty) { skip_empty() }}, expectation = handle_expectation, packageNotFoundError = function(e) { if (on_cran()) { skip(paste0("{", e$package, "} is not installed.")) }}, snapshot_on_cran = function(cnd) { snapshot_skipped <<- TRUE invokeRestart("muffle_cran_snapshot")}, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error, interrupt = handle_interrupt), error = handle_fatal)
31: doWithOneRestart(return(expr), restart)
32: withOneRestart(expr, restarts[[1L]])
33: withRestarts(tryCatch(withCallingHandlers({ eval(code, test_env) new_expectations <- the$test_expectations > starting_expectations if (snapshot_skipped) { skip("On CRAN") } else if (!new_expectations && skip_on_empty) { skip_empty() }}, expectation = handle_expectation, packageNotFoundError = function(e) { if (on_cran()) { skip(paste0("{", e$package, "} is not installed.")) }}, snapshot_on_cran = function(cnd) { snapshot_skipped <<- TRUE invokeRestart("muffle_cran_snapshot")}, skip = handle_skip, warning = handle_warning, message = handle_message, error = handle_error, interrupt = handle_interrupt), error = handle_fatal), end_test = function() { })
34: test_code(code = exprs, env = env, reporter = get_reporter() %||% StopReporter$new())
35: source_file(path, env = env(env), desc = desc, shuffle = shuffle, error_call = error_call)
36: FUN(X[[i]], ...)
37: lapply(test_paths, test_one_file, env = env, desc = desc, shuffle = shuffle, error_call = error_call)
38: doTryCatch(return(expr), name, parentenv, handler)
39: tryCatchOne(expr, names, parentenv, handlers[[1L]])
40: tryCatchList(expr, classes, parentenv, handlers)
41: tryCatch(code, testthat_abort_reporter = function(cnd) { cat(conditionMessage(cnd), "\n") NULL})
42: with_reporter(reporters$multi, lapply(test_paths, test_one_file, env = env, desc = desc, shuffle = shuffle, error_call = error_call))
43: test_files_serial(test_dir = test_dir, test_package = test_package, test_paths = test_paths, load_helpers = load_helpers, reporter = reporter, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, desc = desc, load_package = load_package, shuffle = shuffle, error_call = error_call)
44: test_files(test_dir = path, test_paths = test_paths, test_package = package, reporter = reporter, load_helpers = load_helpers, env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning, load_package = load_package, parallel = parallel, shuffle = shuffle)
45: test_dir("testthat", package = package, reporter = reporter, ..., load_package = "installed")
46: test_check("pprof")
An irrecoverable exception occurred. R is aborting now ...
Segmentation fault
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.0.3
Check: examples
Result: ERROR
Running examples in ‘pprof-Ex.R’ failed
The error most likely occurred in:
> ### Name: SM_output.logis_re
> ### Title: Calculate direct/indirect standardized ratios/rates from a
> ### fitted 'logis_re' object
> ### Aliases: SM_output.logis_re
>
> ### ** Examples
>
> data(ExampleDataBinary)
> outcome = ExampleDataBinary$Y
> covar = ExampleDataBinary$Z
> ProvID = ExampleDataBinary$ProvID
> fit_re <- logis_re(Y = outcome, Z = covar, ProvID = ProvID)
Input format: Y, Z, and ProvID.
Error: Downdated VtV is not positive definite
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 1.0.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [83s/83s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-confint-132.R
Saving _problems/test-confint-165.R
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Saving _problems/test-logis_cre-13.R
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: data, Y.char, Z.char, and ProvID.char.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: formula and data.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Saving _problems/test-logis_re-14.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-summary-90.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-test-106.R
Saving _problems/test-test-129.R
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 138 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-confint.R:132:3'): test.logis_re function behaves correctly ────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-confint.R:132:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-confint.R:165:3'): test.logis_cre function behaves correctly ───
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-confint.R:165:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-logis_cre.R:13:3'): logis_cre function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-logis_cre.R:13:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-logis_re.R:14:3'): logis_re function behaves correctly ─────────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(...) at test-logis_re.R:14:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. └─lme4:::deriv12(fn, opt$par, fx = opt$value)
6. └─lme4 (local) fun(xss, ...)
7. └─lme4 (local) pwrssUpdate(...)
── Error ('test-summary.R:90:3'): summary.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-summary.R:90:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:106:3'): test.logis_re function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-test.R:106:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:129:3'): test.logis_cre function behaves correctly ──────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-test.R:129:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 138 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.0.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [49s/54s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-confint-165.R
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Saving _problems/test-logis_cre-13.R
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: data, Y.char, Z.char, and ProvID.char.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: formula and data.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Saving _problems/test-logis_re-14.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-summary-90.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-test-106.R
Saving _problems/test-test-129.R
[ FAIL 6 | WARN 0 | SKIP 0 | PASS 147 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-confint.R:165:3'): test.logis_cre function behaves correctly ───
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-confint.R:165:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-logis_cre.R:13:3'): logis_cre function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-logis_cre.R:13:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-logis_re.R:14:3'): logis_re function behaves correctly ─────────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(...) at test-logis_re.R:14:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-summary.R:90:3'): summary.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-summary.R:90:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:106:3'): test.logis_re function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-test.R:106:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:129:3'): test.logis_cre function behaves correctly ──────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-test.R:129:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
[ FAIL 6 | WARN 0 | SKIP 0 | PASS 147 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 1.0.3
Check: examples
Result: ERROR
Running examples in 'pprof-Ex.R' failed
The error most likely occurred in:
> ### Name: SM_output.logis_cre
> ### Title: Calculate direct/indirect standardized ratios/rates from a
> ### fitted 'logis_cre' object
> ### Aliases: SM_output.logis_cre
>
> ### ** Examples
>
> data(ExampleDataBinary)
> outcome <- ExampleDataBinary$Y
> covar <- ExampleDataBinary$Z
> ProvID <- ExampleDataBinary$ProvID
> data <- data.frame(outcome, ProvID, covar)
> outcome.char <- colnames(data)[1]
> ProvID.char <- colnames(data)[2]
> wb.char <- c("z1", "z2")
> other.char <- c("z3", "z4", "z5")
> fit_cre <- logis_cre(data = data, Y.char = outcome.char, ProvID.char = ProvID.char,
+ wb.char = wb.char, other.char = other.char)
Flavors: r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64
Version: 1.0.3
Check: tests
Result: ERROR
Running 'testthat.R' [18s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Flavor: r-devel-windows-x86_64
Version: 1.0.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [80s/112s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-SM_output-99.R
Saving _problems/test-SM_output-125.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-confint-132.R
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Saving _problems/test-logis_cre-13.R
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: data, Y.char, Z.char, and ProvID.char.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: formula and data.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-summary-90.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-test-106.R
[ FAIL 6 | WARN 0 | SKIP 0 | PASS 141 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-SM_output.R:99:3'): SM_output.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-SM_output.R:99:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-SM_output.R:125:3'): SM_output.logis_cre function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-SM_output.R:125:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-confint.R:132:3'): test.logis_re function behaves correctly ────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-confint.R:132:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-logis_cre.R:13:3'): logis_cre function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-logis_cre.R:13:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-summary.R:90:3'): summary.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-summary.R:90:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:106:3'): test.logis_re function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-test.R:106:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
[ FAIL 6 | WARN 0 | SKIP 0 | PASS 141 ]
Error:
! Test failures.
Execution halted
Flavor: r-patched-linux-x86_64
Version: 1.0.3
Check: examples
Result: ERROR
Running examples in ‘pprof-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: SM_output.logis_re
> ### Title: Calculate direct/indirect standardized ratios/rates from a
> ### fitted 'logis_re' object
> ### Aliases: SM_output.logis_re
>
> ### ** Examples
>
> data(ExampleDataBinary)
> outcome = ExampleDataBinary$Y
> covar = ExampleDataBinary$Z
> ProvID = ExampleDataBinary$ProvID
> fit_re <- logis_re(Y = outcome, Z = covar, ProvID = ProvID)
Input format: Y, Z, and ProvID.
Error: Downdated VtV is not positive definite
Execution halted
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
SM_output.logis_cre 13.986 0.067 21.058
Flavor: r-release-linux-x86_64
Version: 1.0.3
Check: tests
Result: ERROR
Running ‘testthat.R’ [70s/108s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-SM_output-99.R
Saving _problems/test-SM_output-125.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-confint-132.R
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
Input format: data, Y.char, Z.char, and ProvID.char.
Input format: formula and data.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: data, Y.char, Z.char, and ProvID.char.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: formula and data.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-logis_re-13.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-summary-90.R
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Saving _problems/test-test-106.R
Saving _problems/test-test-129.R
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 139 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-SM_output.R:99:3'): SM_output.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-SM_output.R:99:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-SM_output.R:125:3'): SM_output.logis_cre function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-SM_output.R:125:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-confint.R:132:3'): test.logis_re function behaves correctly ────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-confint.R:132:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-logis_re.R:13:3'): logis_re function behaves correctly ─────────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-logis_re.R:13:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-summary.R:90:3'): summary.logis_re function behaves correctly ──
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-summary.R:90:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:106:3'): test.logis_re function behaves correctly ───────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_re(Y = Y, Z = Z, ProvID = ProvID) at test-test.R:106:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
── Error ('test-test.R:129:3'): test.logis_cre function behaves correctly ──────
<Rcpp::exception/C++Error/error/condition>
Error: Downdated VtV is not positive definite
Backtrace:
▆
1. └─pprof::logis_cre(...) at test-test.R:129:3
2. └─lme4::glmer(...)
3. └─lme4::optimizeGlmer(...)
4. └─lme4:::optwrap(...)
5. ├─base::withCallingHandlers(...)
6. ├─base::do.call(optfun, arglist)
7. └─lme4 (local) `<fn>`(...)
8. ├─nM$newf(fn(nM$xeval()))
9. │ └─base::stopifnot(length(value <- as.numeric(value)) == 1L)
10. └─lme4 (local) fn(nM$xeval())
11. └─lme4 (local) pwrssUpdate(...)
[ FAIL 7 | WARN 0 | SKIP 0 | PASS 139 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-linux-x86_64
Version: 1.0.3
Check: tests
Result: ERROR
Running 'testthat.R' [10s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Flavor: r-release-windows-x86_64
Version: 1.0.3
Check: tests
Result: ERROR
Running 'testthat.R' [12s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(pprof)
>
> test_check("pprof")
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
Input format: Y, Z, and ProvID.
3 out of 100 remaining providers with no events.
0 out of 100 remaining providers with all events.
After screening, 38.77% of all records exhibit occurrences of events (Y = 1)
Implementing SerBIN algorithm (Rcpp) for fixed provider effects model ...
Iter 1: Minimum criterion across all checks is 5.022e-01;
Iter 2: Minimum criterion across all checks is 1.422e-01;
Iter 3: Minimum criterion across all checks is 3.528e-02;
Iter 4: Minimum criterion across all checks is 5.671e-03;
Iter 5: Minimum criterion across all checks is 1.214e-03;
Iter 6: Minimum criterion across all checks is 2.151e-04;
Iter 7: Minimum criterion across all checks is 6.647e-05;
Iter 8: Minimum criterion across all checks is 7.565e-06;
serBIN (Rcpp) algorithm converged after 8 iterations!
Setting levels: control = 0, case = 1
Setting direction: controls < cases
Input format: Y, Z, and ProvID.
Flavor: r-oldrel-windows-x86_64
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