Last updated on 2025-12-03 05:50:47 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| boxcoxmix | 13 | ||
| clusterCrit | 13 | ||
| GramQuad | 2 | 11 | |
| kedd | 2 | 11 | |
| trouBBlme4SolveR | 3 | 10 |
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: NOTE: 2, OK: 11
Version: 0.1.1
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Iago Giné-Vázquez <iago.gin-vaz@protonmail.com>’
The Description field contains
<arXiv:2106.14875> [math.NA] 28 Jun 2021, by Irfan Muhammad [School of
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Current CRAN status: NOTE: 2, OK: 11
Version: 1.0.4
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Iago Giné-Vázquez <iago.gin-vaz@protonmail.com>’
The Description field contains
in Arsalane Chouaib Guidoum (2020) <arXiv:2012.06102> [stat.CO]).
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Current CRAN status: ERROR: 3, OK: 10
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