Hi, All: Does 'nlme' require the nonlinear function to be differentiable? I'm fitting structural change models to many related time series, and I'd like to improve the estimates of the change point times through some type of pooling. Unfortunately, I've so far been unable to get 'nlme' to work for me. The following toy example is the closest I've come to what I want using 'nlme': library(nlme) tstDF5 <- data.frame(t.=rep(1:5, 3), subj=rep(1:3, e=5), y=c(rep(0:1, c(1,4)), rep(0:1, c(2,3)), rep(0:1, c(3,2)) ) ) breakpoint0seg2t <- function(t., lT){ t1 <- 5*plogis(-lT) ((t.<=t1)+(t1<t.)) } tstFit <- nlme(y~breakpoint0seg2t(t., lT1), data=tstDF5, fixed=lT1~1, random=list(subj=pdDiag(l1~1)), start=0 ) Error in chol((value + t(value))/2) : the leading minor of order 1 is not positive definite The function 'breakpoint0seg2t' is constant except at the data points, where it is discontinuous. Is this error message generated by the fact that the first derivative of 'breakpoint0seg2t' is 0 almost everywhere? If yes, what are the options for getting around this? The real problem behind this toy example involves fitting either step functions or linear or quadratics in time with any number of breakpoints. I'm currently estimating the required parameters using the 'strucchange' package. That work, but I'm having trouble with this enhancement. Thanks, Spencer Graves