Hi, I'm trying to fit a LMER to Gamma distributed data using the identity link function, but keep running into the problem that a negative mean is estimated: > lmer(y~x+(1|s), data, family=Gamma(link="identity"), verbose=TRUE) 0: 303489.72: 0.0118042 5.95694 -0.0360192 1: 206240.18: 0.990220 6.16357 -0.0381219 Error in mer_finalize(ans) : mu[i] must be positive: mu = 2.63294e-309, i = 1788870688 Fitting a GLM works fine. I tried taking its coefficients as start values for the LMER, but that made no difference: > m <- glm(y~x, data, family=Gamma(link="identity")) > lmer(y~x+(1|s), data, family=Gamma(link="identity"), start=coefficients(m), verbose=TRUE) 0: 303489.72: 0.0118042 5.95694 -0.0360192 1: 206240.18: 0.990220 6.16357 -0.0381219 Error in mer_finalize(ans) : mu[i] must be positive: mu = 2.63293e-309, i = 1778647072 What could be going on, and what can I do about it? R version 2.9.2 (2009-08-24) on Windows lme4 version 0.999375-32 Best, Stefan Frank Institute for Logic, Language and Computation University of Amsterdam URL: staff.science.uva.nl/~sfrank Tel: +31 20 5256054 Visiting address: Postal address: Science Park 904, Room C3.123 P.O. Box 94242 Amsterdam 1090 GE Amsterdam The Netherlands The Netherlands
Error "mu[i] must be positive" with Gamma family
1 message · Stefan Frank