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Fitting repeated measures in R, convergence issues. I have the following fit which is one of many datasets and it doesn't converge. I do other sets that do. This dataset and model work in SAS... Could I get some direction in what to do to have this work in R? Things to look at (matrices,option settings,a reference on this topic for r/splus ...).

fit.gls <- gls(resp~grpnum+grpnum/day,data=long, corr=cormat,na.action=na.omit)
Error in glsEstimate(object, control = control) : 
  computed "gls" fit is singular, rank 62

I have read the following and still trying to work thru it... Converting Repeated Measures mixed model formula from SAS to R

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user2945234
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1 Answers1

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The problem is the data. gls needs to invert a matrix to work (see Wikipedia for the formula to estimate the covariates). For you particular data set, that matrix is not invertible.

You can allow for singular values to be allowed with the control argument:

fit.gls <- gls(resp~grpnum+grpnum/day,data=long, corr=cormat,na.action=na.omit, control = list(singular.ok = TRUE))

Be careful with this as you may get bad results! Always check the model fit afterwards.

Look at the help for gls and glsConrol for more details about options.

Christopher Louden
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