CRAN Package Check Results for Package movieROC

Last updated on 2026-09-07 05:51:21 CEST.

Flavor	Version	Tinstall	Tcheck	Ttotal	Status	Flags
r-devel-linux-x86_64-debian-clang	0.1.2	14.88	136.82	151.70	OK
r-devel-linux-x86_64-debian-gcc	0.1.2	13.18	94.52	107.70	ERROR
r-devel-linux-x86_64-fedora-clang	0.1.2	13.00	88.96	101.96	ERROR
r-devel-linux-x86_64-fedora-gcc	0.1.2	12.00	92.76	104.76	ERROR
r-devel-windows-x86_64	0.1.2	20.00	146.00	166.00	OK
r-patched-linux-x86_64	0.1.2	17.66	132.09	149.75	OK
r-release-linux-x86_64	0.1.2	14.59	132.37	146.96	OK
r-release-macos-arm64	0.1.2	4.00	36.00	40.00	OK
r-release-macos-x86_64	0.1.2	12.00	137.00	149.00	OK
r-release-windows-x86_64	0.1.2	19.00	141.00	160.00	OK
r-oldrel-macos-arm64	0.1.2				OK
r-oldrel-macos-x86_64	0.1.2	11.00	136.00	147.00	OK
r-oldrel-windows-x86_64	0.1.2	27.00	181.00	208.00	OK

Check Details

Version: 0.1.2
Check: examples
Result: ERROR Running examples in ‘movieROC-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: multiROC > ### Title: Build a ROC curve for a multivariate marker with dimension p > ### Aliases: multiROC multiROC.default > > ### ** Examples > > data(HCC) > > # ROC curve for genes 20202438 and 18384097 (p=2) to identify tumor by 4 different methods: > X <- cbind(HCC$cg20202438, HCC$cg18384097); D <- HCC$tumor > ## 1. Linear combinations with fixed parameters by Pepe and Thompson (2000) > multiROC(X, D, method = "fixedLinear", methodLinear = "PepeThompson") Data was encoded with nontumor (controls) and tumor (cases). There are 62 controls and 62 cases. A total of 2 variables have been considered. A linear combination with fixed parameters estimated by PepeThompson approach has been considered. The specificity and sensitivity reported by the Youden index are 0.871 and 0.548, respectively, corresponding to the cut-off point 0.358 for the transformation h(X) = - 0.51*X.1 + 1*X.2. The area under the ROC curve (AUC) is 0.697. > ## 2.Linear combinations with dynamic parameters by Meisner et al. (2021) > ## 3. Logistic regression model with quadratic formula by default > multiROC(X, D) Error in as.data.frame.default(data) : cannot coerce class ‘"formula"’ to a data.frame Calls: multiROC ... model.frame.default -> as.data.frame -> as.data.frame.default Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1.2
Check: examples
Result: ERROR Running examples in ‘movieROC-Ex.R’ failed The error most likely occurred in: > ### Name: multiROC > ### Title: Build a ROC curve for a multivariate marker with dimension p > ### Aliases: multiROC multiROC.default > > ### ** Examples > > data(HCC) > > # ROC curve for genes 20202438 and 18384097 (p=2) to identify tumor by 4 different methods: > X <- cbind(HCC$cg20202438, HCC$cg18384097); D <- HCC$tumor > ## 1. Linear combinations with fixed parameters by Pepe and Thompson (2000) > multiROC(X, D, method = "fixedLinear", methodLinear = "PepeThompson") Data was encoded with nontumor (controls) and tumor (cases). There are 62 controls and 62 cases. A total of 2 variables have been considered. A linear combination with fixed parameters estimated by PepeThompson approach has been considered. The specificity and sensitivity reported by the Youden index are 0.871 and 0.548, respectively, corresponding to the cut-off point 0.358 for the transformation h(X) = - 0.51*X.1 + 1*X.2. The area under the ROC curve (AUC) is 0.697. > ## 2.Linear combinations with dynamic parameters by Meisner et al. (2021) > ## 3. Logistic regression model with quadratic formula by default > multiROC(X, D) Error in as.data.frame.default(data) : cannot coerce class ‘"formula"’ to a data.frame Calls: multiROC ... model.frame.default -> as.data.frame -> as.data.frame.default Execution halted Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc