Hi Kathie, The gradient check in "optimx" checks if the user specified gradient (at starting parameters) is within roughly 1.e-05 * (1 + fval) of the numerically computed gradient. It is likely that you have correctly coded up the gradient, but still there can be significant differences b/w numerical and exact gradients. This can happen when the gradients are very large.
I would check this again separately as follows: require(numDeriv) mygrad <- gr.fy(theta0) numgrad <- grad(x=theta0, func=gr.fy) cbind(mygrad, numgrad) all.equal(mygrad, numgrad) Can you report these gradients to us? In "optimx", we should probably change this into a "warning" rather than a "stop". Ravi. ------------------------------------------------------- Ravi Varadhan, Ph.D. Assistant Professor, Division of Geriatric Medicine and Gerontology School of Medicine Johns Hopkins University Ph. (410) 502-2619 email: rvarad...@jhmi.edu ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
