Hi Julia-users, I am trying to run a few simple regressions on simulated data. I had no problem with a logit and was able to run it using glm and subsequently match the results with a separate maximum likelihood. I'm having a lot more trouble with the probit which doesn't seem to want to converge using glm. Stata has no problem with convergence to the true parameters with the same data. The simulated data are assumed to come from an underlying latent variable.
Thanks in advance for any insights, Andrew ********* using DataFrames using Distributions using GLM srand(10001) N=10000 genX = Normal(0,3) genɛ = Normal() X = rand(genX,N) ɛ = rand(genɛ,N) α0 = 2 α1 = -1 Ystar = α0 + α1*X + ɛ Y = (Ystar.>0)*1. df = DataFrame(X=[X],Y=[Y]) Probit = glm(Y ~ X, df, Binomial(), ProbitLink())
