Why does nlme::getVarCov not Work for nlme Models?
1. The Help page for getVarCov says that it supports lme and gls models only. So not nonlinear models. As to why it does not, that is off topic here, as that is a statistical question. 2. As this is longstanding, it almost certainly has good reason for being there, so I would seriously doubt it. But of course I don't speak for R Core. Cheers, Bert
On Mon, Nov 18, 2019 at 9:43 PM <bill at denney.ws> wrote:
Hi, I was just trying to summarize an nlme model using `broom.mixed::tidy()`, and it doesn't give random effects or residual variability for nlme models. As I looked deeper, this appears to be related to the fact that `nlme::getVarCorr()` doesn't support nlme models for no reason that I can discern [1]. I do see that it simply has a `stop()` call if the model is nlme, but I don't know or see a commented reason why this would be. I can imagine that in a nonlinear model the interpretation of variance is different than in a linear model (namely that it is more likely to be asymmetric and this result is asymptotic), but that doesn't seem like a reason to prevent the use of the tool. When I pretended that my model was an lme model (set the class temporarily to "lme"), it gave the expected result. My questions are: 1. Why does nlme::getVarCorr() not support nlme models? 2. If there is not a known reason, does someone in R-core think that a patch removing the stop below [1] would be accepted? [1] https://svn.r-project.org/R-packages/trunk/nlme/R/VarCov.R the lines are: if(any("nlme" == class(obj))) stop("not implemented for \"nlme\" objects") Thanks, Bill [[alternative HTML version deleted]]
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