Last updated on 2025-09-12 17:54:28 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0.0 | 1.80 | 23.89 | 25.69 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.0.0 | 1.62 | 19.63 | 21.25 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.0.0 | 38.47 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.0.0 | 36.28 | ERROR | |||
| r-devel-windows-x86_64 | 1.0.0 | 3.00 | 43.00 | 46.00 | OK | |
| r-patched-linux-x86_64 | 1.0.0 | 2.05 | 22.30 | 24.35 | OK | |
| r-release-linux-x86_64 | 1.0.0 | 1.56 | 21.97 | 23.53 | OK | |
| r-release-macos-arm64 | 1.0.0 | 32.00 | OK | |||
| r-release-macos-x86_64 | 1.0.0 | 27.00 | OK | |||
| r-release-windows-x86_64 | 1.0.0 | 3.00 | 43.00 | 46.00 | OK | |
| r-oldrel-macos-arm64 | 1.0.0 | 18.00 | OK | |||
| r-oldrel-macos-x86_64 | 1.0.0 | 26.00 | OK | |||
| r-oldrel-windows-x86_64 | 1.0.0 | 4.00 | 48.00 | 52.00 | OK |
Version: 1.0.0
Check: examples
Result: ERROR
Running examples in ‘forestPSD-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: psdfun
> ### Title: Regression analysis for survival curves.
> ### Aliases: psdfun
>
> ### ** Examples
>
> data(Npop)
> psd_D1<-psdfun(ax=Npop$ax,index="Deevey1")
> psd_D1
$Summary
Formula: ax ~ a + b * age
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 5603.9 1062.0 5.277 0.000509 ***
b -642.3 156.6 -4.102 0.002669 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 1642 on 9 degrees of freedom
Number of iterations to convergence: 2
Achieved convergence tolerance: 1.49e-08
$Goodness
MSE RMSE Rsquare adj.Rsquare MAE MAPE RASE AIC
1 2206682 1485.49 0.6515192 0.564399 1234.35 17.69146 0.7053431 197.8937
BIC
1 197.8937
$Data
age ageclass ax predict
1 1 I 8283 4961.5455
2 2 II 5238 4319.2364
3 3 III 1921 3676.9273
4 4 IV 1425 3034.6182
5 5 V 926 2392.3091
6 6 VI 659 1750.0000
7 7 VII 479 1107.6909
8 8 VIII 228 465.3818
9 9 IX 57 -176.9273
10 10 X 24 -819.2364
11 11 XI 10 -1461.5455
> psd_D2<-psdfun(ax=Npop$ax,index="Deevey2")
> psd_D2
$Summary
Formula: ax ~ a * exp(-b * age)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 1.504e+04 9.717e+02 15.48 8.59e-08 ***
b 5.828e-01 3.883e-02 15.01 1.12e-07 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 318.7 on 9 degrees of freedom
Number of iterations to convergence: 17
Achieved convergence tolerance: 1.49e-08
$Goodness
MSE RMSE Rsquare adj.Rsquare MAE MAPE RASE AIC
1 83111.3 288.2903 0.9869709 0.9837137 188.8823 0.4079135 0.1079327 161.8239
BIC
1 161.8239
$Data
age ageclass ax predict
1 1 I 8283 8396.40389
2 2 II 5238 4687.87598
3 3 III 1921 2617.33255
4 4 IV 1425 1461.30779
5 5 V 926 815.87663
6 6 VI 659 455.51983
7 7 VII 479 254.32560
8 8 VIII 228 141.99494
9 9 IX 57 79.27854
10 10 X 24 44.26276
11 11 XI 10 24.71276
> psd_D3<-psdfun(ax=Npop$ax,index="Deevey3")
> psd_D3
$Summary
Formula: ax ~ a * (age^-b)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 8691.1232 633.3189 13.723 2.44e-07 ***
b 1.2598 0.1326 9.499 5.48e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 649 on 9 degrees of freedom
Number of iterations to convergence: 18
Achieved convergence tolerance: 1.49e-08
$Goodness
MSE RMSE Rsquare adj.Rsquare MAE MAPE RASE AIC
1 344662.5 587.0797 0.9491095 0.9363869 442.1638 6.578955 0.252665 177.4702
BIC
1 177.4702
$Data
age ageclass ax predict
1 1 I 8283 8691.1232
2 2 II 5238 3629.4310
3 3 III 1921 2177.7043
4 4 IV 1425 1515.6579
5 5 V 926 1144.2318
6 6 VI 659 909.4138
7 7 VII 479 748.8969
8 8 VIII 228 632.9419
9 9 IX 57 545.6597
10 10 X 24 477.8336
11 11 XI 10 423.7700
> library(ggplot2)
> psdnls.p<-ggplot()+geom_bar(aes(x=age,y=ax,group=ageclass),data=psd_D2$Data,stat = "identity")+
+ geom_line(aes(x=age,y=predict),color="blue",linewidth=1,data=psd_D2$Data)+
+ geom_text(aes(x=10,y=7700),label=expression(paste(italic(y),"=aexp(-b",italic(x),")")))+
+ geom_text(aes(x=10,y=7300),label=expression(paste(R^2,"=0.987")))+
+ scale_x_continuous(breaks=1:11)+
+ scale_x_discrete(limits=psd_D2$Data$ageclass)+
+ xlab("Age class")+ylab("Number of individuals")
Scale for x is already present.
Adding another scale for x, which will replace the existing scale.
> psdnls.p
Error in `geom_text()`:
! Problem while setting up geom aesthetics.
ℹ Error occurred in the 3rd layer.
Caused by error in `list_sizes()`:
! `x$label` must be a vector, not an expression vector.
Backtrace:
▆
1. ├─base (local) `<fn>`(x)
2. ├─ggplot2 (local) `print.ggplot2::ggplot`(x)
3. │ ├─ggplot2::ggplot_build(x)
4. │ └─ggplot2 (local) `ggplot_build.ggplot2::ggplot`(x)
5. │ └─ggplot2:::by_layer(...)
6. │ ├─rlang::try_fetch(...)
7. │ │ ├─base::tryCatch(...)
8. │ │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. │ │ └─base::withCallingHandlers(...)
12. │ └─ggplot2 (local) f(l = layers[[i]], d = data[[i]])
13. │ └─l$compute_geom_2(d, theme = plot@theme)
14. │ └─ggplot2 (local) compute_geom_2(..., self = self)
15. │ └─self$geom$use_defaults(...)
16. │ └─ggplot2 (local) use_defaults(..., self = self)
17. │ └─ggplot2:::check_aesthetics(new_params, nrow(data))
18. │ └─vctrs::list_sizes(x)
19. └─vctrs:::stop_scalar_type(`<fn>`(`<expression>`), "x$label", `<env>`)
20. └─vctrs:::stop_vctrs(...)
21. └─rlang::abort(message, class = c(class, "vctrs_error"), ..., call = call)
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.0.0
Check: dependencies in R code
Result: NOTE
Namespaces in Imports field not imported from:
‘ggplot2’ ‘reshape2’
All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 1.0.0
Check: examples
Result: ERROR
Running examples in ‘forestPSD-Ex.R’ failed
The error most likely occurred in:
> ### Name: psdfun
> ### Title: Regression analysis for survival curves.
> ### Aliases: psdfun
>
> ### ** Examples
>
> data(Npop)
> psd_D1<-psdfun(ax=Npop$ax,index="Deevey1")
> psd_D1
$Summary
Formula: ax ~ a + b * age
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 5603.9 1062.0 5.277 0.000509 ***
b -642.3 156.6 -4.102 0.002669 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 1642 on 9 degrees of freedom
Number of iterations to convergence: 2
Achieved convergence tolerance: 1.49e-08
$Goodness
MSE RMSE Rsquare adj.Rsquare MAE MAPE RASE AIC
1 2206682 1485.49 0.6515192 0.564399 1234.35 17.69146 0.7053431 197.8937
BIC
1 197.8937
$Data
age ageclass ax predict
1 1 I 8283 4961.5455
2 2 II 5238 4319.2364
3 3 III 1921 3676.9273
4 4 IV 1425 3034.6182
5 5 V 926 2392.3091
6 6 VI 659 1750.0000
7 7 VII 479 1107.6909
8 8 VIII 228 465.3818
9 9 IX 57 -176.9273
10 10 X 24 -819.2364
11 11 XI 10 -1461.5455
> psd_D2<-psdfun(ax=Npop$ax,index="Deevey2")
> psd_D2
$Summary
Formula: ax ~ a * exp(-b * age)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 1.504e+04 9.717e+02 15.48 8.59e-08 ***
b 5.828e-01 3.883e-02 15.01 1.12e-07 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 318.7 on 9 degrees of freedom
Number of iterations to convergence: 17
Achieved convergence tolerance: 1.49e-08
$Goodness
MSE RMSE Rsquare adj.Rsquare MAE MAPE RASE AIC
1 83111.3 288.2903 0.9869709 0.9837137 188.8823 0.4079135 0.1079327 161.8239
BIC
1 161.8239
$Data
age ageclass ax predict
1 1 I 8283 8396.40389
2 2 II 5238 4687.87598
3 3 III 1921 2617.33255
4 4 IV 1425 1461.30779
5 5 V 926 815.87663
6 6 VI 659 455.51983
7 7 VII 479 254.32560
8 8 VIII 228 141.99494
9 9 IX 57 79.27854
10 10 X 24 44.26276
11 11 XI 10 24.71276
> psd_D3<-psdfun(ax=Npop$ax,index="Deevey3")
> psd_D3
$Summary
Formula: ax ~ a * (age^-b)
Parameters:
Estimate Std. Error t value Pr(>|t|)
a 8691.1232 633.3189 13.723 2.44e-07 ***
b 1.2598 0.1326 9.499 5.48e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 649 on 9 degrees of freedom
Number of iterations to convergence: 18
Achieved convergence tolerance: 1.49e-08
$Goodness
MSE RMSE Rsquare adj.Rsquare MAE MAPE RASE AIC
1 344662.5 587.0797 0.9491095 0.9363869 442.1638 6.578955 0.252665 177.4702
BIC
1 177.4702
$Data
age ageclass ax predict
1 1 I 8283 8691.1232
2 2 II 5238 3629.4310
3 3 III 1921 2177.7043
4 4 IV 1425 1515.6579
5 5 V 926 1144.2318
6 6 VI 659 909.4138
7 7 VII 479 748.8969
8 8 VIII 228 632.9419
9 9 IX 57 545.6597
10 10 X 24 477.8336
11 11 XI 10 423.7700
> library(ggplot2)
> psdnls.p<-ggplot()+geom_bar(aes(x=age,y=ax,group=ageclass),data=psd_D2$Data,stat = "identity")+
+ geom_line(aes(x=age,y=predict),color="blue",linewidth=1,data=psd_D2$Data)+
+ geom_text(aes(x=10,y=7700),label=expression(paste(italic(y),"=aexp(-b",italic(x),")")))+
+ geom_text(aes(x=10,y=7300),label=expression(paste(R^2,"=0.987")))+
+ scale_x_continuous(breaks=1:11)+
+ scale_x_discrete(limits=psd_D2$Data$ageclass)+
+ xlab("Age class")+ylab("Number of individuals")
Scale for x is already present.
Adding another scale for x, which will replace the existing scale.
> psdnls.p
Error in `geom_text()`:
! Problem while setting up geom aesthetics.
ℹ Error occurred in the 3rd layer.
Caused by error in `list_sizes()`:
! `x$label` must be a vector, not an expression vector.
Backtrace:
▆
1. ├─base (local) `<fn>`(x)
2. ├─ggplot2 (local) `print.ggplot2::ggplot`(x)
3. │ ├─ggplot2::ggplot_build(x)
4. │ └─ggplot2 (local) `ggplot_build.ggplot2::ggplot`(x)
5. │ └─ggplot2:::by_layer(...)
6. │ ├─rlang::try_fetch(...)
7. │ │ ├─base::tryCatch(...)
8. │ │ │ └─base (local) tryCatchList(expr, classes, parentenv, handlers)
9. │ │ │ └─base (local) tryCatchOne(expr, names, parentenv, handlers[[1L]])
10. │ │ │ └─base (local) doTryCatch(return(expr), name, parentenv, handler)
11. │ │ └─base::withCallingHandlers(...)
12. │ └─ggplot2 (local) f(l = layers[[i]], d = data[[i]])
13. │ └─l$compute_geom_2(d, theme = plot@theme)
14. │ └─ggplot2 (local) compute_geom_2(..., self = self)
15. │ └─self$geom$use_defaults(...)
16. │ └─ggplot2 (local) use_defaults(..., self = self)
17. │ └─ggplot2:::check_aesthetics(new_params, nrow(data))
18. │ └─vctrs::list_sizes(x)
19. └─vctrs:::stop_scalar_type(`<fn>`(`<expression>`), "x$label", `<env>`)
20. └─vctrs:::stop_vctrs(...)
21. └─rlang::abort(message, class = c(class, "vctrs_error"), ..., call = call)
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
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