search for: nonidentifiable

Folks: In the following mixed effect model, the "x" and residual variance components are nonidentifiable. Yet lme() (or the equivalent in lmer()) happily produces an answer in which the sum of the variance components is the correct estimate of the single variance parameter. Why? -- i.e. why doesn't lme complain? x <- 1:50 y <- rnorm(50) m1 <- lme( y ~ 1, rand = ~1|x) Many thanks, Bert...

I am running the following nls equation. I tried it with data that excel was fitting and got the error: singular gradient matrix at initial parameter estimates I thought it was due to a low number of points (6), but when I create a dataset, I get the same problem. If I remove the parameter "a," then it can find a solution. Does anyone know what I can do to fit this model?