[R-sig-ME] convergence issues on lme4 and incoherent error messages

[Cristiano Alessandro]

Hi all,

I am having trouble fitting a mixed effect model. I keep getting the
following warning, independently on the optimizer that I use (I tried
almost all of them):

Warning messages:
1: 'rBind' is deprecated.
 Since R version 3.2.0, base's rbind() should work fine with S4 objects
2: In optimx.check(par, optcfg$ufn, optcfg$ugr, optcfg$uhess, lower,  :
  Parameters or bounds appear to have different scalings.
  This can cause poor performance in optimization.
  It is important for derivative free methods like BOBYQA, UOBYQA, NEWUOA.
3: Model failed to converge with 5 negative eigenvalues: -2.5e-01 -5.8e-01
-8.2e+01 -9.5e+02 -1.8e+03

This suggests that the optimization did not converge. On the other hand, if
I call summary() of the "fitted" model, I receive (among the other things)
a convergence code = 0, which according to the documentation means that the
optimization has indeed converged. Did the optimization converged or not?

convergence code: 0
Parameters or bounds appear to have different scalings.
  This can cause poor performance in optimization.
  It is important for derivative free methods like BOBYQA, UOBYQA, NEWUOA.

Note that I used 'optimx' ("L-BFGS-B") for this specific run of the
optimization. I also get other weird stuff that I do not understand:
negative entries in the var-cov matrix, which I could not get rid of even
if I simplify the model a lot (see
https://stats.stackexchange.com/questions/408504/variance-covariance-matrix-with-negative-entries-on-mixed-model-fit
, with data). I thought of further simplify the var-cov matrix making it
diagonal, but I am still struggling on how to do that in lme4 (see
https://stats.stackexchange.com/questions/412345/diagonal-var-cov-matrix-for-random-slope-in-lme4
).

Any help is highly appreciated. Thanks!

Cristiano

	[[alternative HTML version deleted]]