Modeling conditional probabilities; using regression to model probabilities; transforming probabilities to work better with regression; the logistic regression model. Maximum likelihood for logistic regression; numerical maximum likelihood by Newton's method and by iteratively re-weighted least squares. Logistic-additive models as a non-parametric alternative (which you should probably use unless you have very definite reasons); bootstrap specification testing for logistic regression.
PDF notes, incorporating R examples
Posted by crshalizi at March 30, 2011 23:01 | permanent link