CRAN Package Check Results for Maintainer ‘Iago Giné-Vázquez <iago.gin-vaz at protonmail.com>’

Last updated on 2025-12-04 09:50:24 CET.

Package	ERROR	NOTE	OK
boxcoxmix			13
clusterCrit			13
GramQuad		2	11
kedd		2	11
trouBBlme4SolveR	6		7

Package boxcoxmix

Current CRAN status: OK: 13

Package clusterCrit

Current CRAN status: OK: 13

Package GramQuad

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

Package kedd

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

Package trouBBlme4SolveR

Current CRAN status: ERROR: 6, OK: 7

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