Last updated on 2025-12-04 09:50:09 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.1.3 | 7.19 | 174.94 | 182.13 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.1.3 | 6.42 | 124.79 | 131.21 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.1.3 | 61.00 | 252.19 | 313.19 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 0.1.3 | 27.00 | 293.59 | 320.59 | ERROR | |
| r-devel-windows-x86_64 | 0.1.3 | 9.00 | 212.00 | 221.00 | OK | |
| r-patched-linux-x86_64 | 0.1.3 | 7.83 | 176.81 | 184.64 | ERROR | |
| r-release-linux-x86_64 | 0.1.2 | 8.42 | 184.24 | 192.66 | OK | |
| r-release-macos-arm64 | 0.1.4 | 2.00 | 56.00 | 58.00 | OK | |
| r-release-macos-x86_64 | 0.1.3 | 9.00 | 210.00 | 219.00 | OK | |
| r-release-windows-x86_64 | 0.1.3 | 10.00 | 207.00 | 217.00 | ERROR | |
| r-oldrel-macos-arm64 | 0.1.3 | 2.00 | 54.00 | 56.00 | OK | |
| r-oldrel-macos-x86_64 | 0.1.3 | 7.00 | 227.00 | 234.00 | OK | |
| r-oldrel-windows-x86_64 | 0.1.3 | 12.00 | 281.00 | 293.00 | ERROR |
Version: 0.1.3
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘introduction.Rnw’ using Sweave
Loading required package: Matrix
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.0964374 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?;Model is nearly unidentifiable: large eigenvalue ratio
- Rescale variables?
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.13305 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
boundary (singular) fit: see help('isSingular')
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Numeric predictors rescaled!!!
The default multilevel model is singular since the between-Day variance for the intercept and the between-SUR.ID variance for the intercepts are zero.
Then, we consider the next model after removing these random effects.
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since the between-Subject variance for the nsexage slope is zero.
Then, we consider the next model after removing this random effect.
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since all the random-effects variances are zero.
Then, we consider the next model after removing the random effects.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?
Numeric predictors rescaled!!!
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.00276091 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Loading required namespace: ggplot2
Warning: Some predictor variables are on very different scales: consider rescaling.
You may also use (g)lmerControl(autoscale = TRUE) to improve numerical stability.
Error: processing vignette 'introduction.Rnw' failed with diagnostics:
chunk 11
Error in dwmw(fit_1, scale = TRUE, verbose = TRUE) :
Too many iterations!! to get the model carat ~ depth + table + price + x + y + z + (1 + price | cut) to converge. Check it!!
--- failed re-building ‘introduction.Rnw’
SUMMARY: processing the following file failed:
‘introduction.Rnw’
Error: Vignette re-building failed.
Execution halted
Flavors: r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64
Version: 0.1.3
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building ‘introduction.Rnw’ using Sweave
Loading required package: Matrix
Warning in (function (fn, par, lower = rep.int(-Inf, n), upper = rep.int(Inf, :
failure to converge in 10000 evaluations
Warning in optwrap(optimizer, devfun, start, rho$lower, control = control, :
convergence code 4 from Nelder_Mead: failure to converge in 10000 evaluations
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.256533 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?;Model is nearly unidentifiable: large eigenvalue ratio
- Rescale variables?
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.132723 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
boundary (singular) fit: see help('isSingular')
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Numeric predictors rescaled!!!
The default multilevel model is singular since the between-Day variance for the intercept and the between-SUR.ID variance for the intercepts are zero.
Then, we consider the next model after removing these random effects.
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since the between-Subject variance for the nsexage slope is zero.
Then, we consider the next model after removing this random effect.
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since all the random-effects variances are zero.
Then, we consider the next model after removing the random effects.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?
Numeric predictors rescaled!!!
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.00276086 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Loading required namespace: ggplot2
Warning: Some predictor variables are on very different scales: consider rescaling.
You may also use (g)lmerControl(autoscale = TRUE) to improve numerical stability.
Error: processing vignette 'introduction.Rnw' failed with diagnostics:
chunk 11
Error in dwmw(fit_1, scale = TRUE, verbose = TRUE) :
Too many iterations!! to get the model carat ~ depth + table + price + x + y + z + (1 + price | cut) to converge. Check it!!
--- failed re-building ‘introduction.Rnw’
SUMMARY: processing the following file failed:
‘introduction.Rnw’
Error: Vignette re-building failed.
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.1.3
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building 'introduction.Rnw' using Sweave
Loading required package: Matrix
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.0955869 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?;Model is nearly unidentifiable: large eigenvalue ratio
- Rescale variables?
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.132726 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
boundary (singular) fit: see help('isSingular')
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Numeric predictors rescaled!!!
The default multilevel model is singular since the between-Day variance for the intercept and the between-SUR.ID variance for the intercepts are zero.
Then, we consider the next model after removing these random effects.
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since the between-Subject variance for the nsexage slope is zero.
Then, we consider the next model after removing this random effect.
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since all the random-effects variances are zero.
Then, we consider the next model after removing the random effects.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?
Numeric predictors rescaled!!!
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.00276077 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Loading required namespace: ggplot2
Warning: Some predictor variables are on very different scales: consider rescaling.
You may also use (g)lmerControl(autoscale = TRUE) to improve numerical stability.
Error: processing vignette 'introduction.Rnw' failed with diagnostics:
chunk 11
Error in dwmw(fit_1, scale = TRUE, verbose = TRUE) :
Too many iterations!! to get the model carat ~ depth + table + price + x + y + z + (1 + price | cut) to converge. Check it!!
--- failed re-building 'introduction.Rnw'
SUMMARY: processing the following file failed:
'introduction.Rnw'
Error: Vignette re-building failed.
Execution halted
Flavor: r-release-windows-x86_64
Version: 0.1.3
Check: re-building of vignette outputs
Result: ERROR
Error(s) in re-building vignettes:
--- re-building 'introduction.Rnw' using Sweave
Loading required package: Matrix
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.0965328 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?;Model is nearly unidentifiable: large eigenvalue ratio
- Rescale variables?
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.13305 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
boundary (singular) fit: see help('isSingular')
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
Numeric predictors rescaled!!!
The default multilevel model is singular since the between-Day variance for the intercept and the between-SUR.ID variance for the intercepts are zero.
Then, we consider the next model after removing these random effects.
Correlation matrix not shown by default, as p = 16 > 12.
Use print(res$value, correlation=TRUE) or
vcov(res$value) if you need it
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since the between-Subject variance for the nsexage slope is zero.
Then, we consider the next model after removing this random effect.
boundary (singular) fit: see help('isSingular')
The default multilevel model is singular since all the random-effects variances are zero.
Then, we consider the next model after removing the random effects.
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model is nearly unidentifiable: very large eigenvalue
- Rescale variables?
Numeric predictors rescaled!!!
Warning in checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
Model failed to converge with max|grad| = 0.00276077 (tol = 0.002, component 1)
See ?lme4::convergence and ?lme4::troubleshooting.
Loading required namespace: ggplot2
Warning: Some predictor variables are on very different scales: consider rescaling.
You may also use (g)lmerControl(autoscale = TRUE) to improve numerical stability.
Error: processing vignette 'introduction.Rnw' failed with diagnostics:
chunk 11
Error in dwmw(fit_1, scale = TRUE, verbose = TRUE) :
Too many iterations!! to get the model carat ~ depth + table + price + x + y + z + (1 + price | cut) to converge. Check it!!
--- failed re-building 'introduction.Rnw'
SUMMARY: processing the following file failed:
'introduction.Rnw'
Error: Vignette re-building failed.
Execution halted
Flavor: r-oldrel-windows-x86_64