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