Last updated on 2025-10-31 13:51:15 CET.
| Package | ERROR | NOTE | OK | 
|---|---|---|---|
| forestGYM | 13 | ||
| forestHES | 13 | ||
| forestPSD | 9 | 4 | |
| forestSAS | 2 | 11 | 
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: ERROR: 9, OK: 4
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, r-patched-linux-x86_64, r-release-linux-x86_64
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, r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64
Current CRAN status: NOTE: 2, OK: 11
Version: 2.0.4
Check: dependencies in R code
Result: NOTE
  Namespaces in Imports field not imported from:
    ‘spatstat’ ‘spatstat.data’
    All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc