summarize.m: Mimics Stata's
normalMLE.m: Estimates normal linear regression with heteroskedastic errors by maximum likelihood.
applyRestr.m: Allows for easy parameter restrictions in optimization problems (co-writen with Jared Ashworth).
clogit.m: Estimates conditional logit regression by maximum likelihood (co-writen with Jared Ashworth).
ologit.m: Estimates the ordered logit model by maximum likelihood.
EM algorithm example: Code to generate data and estimate simple versions of the EM algorithm for estimation of models with discrete type-specific unobserved heterogeneity.
Machine Learning Resources