carlislerainey

# define log-likelihood function
ll.logit <- function(beta, y, X) {
  p <- plogis(X%*%beta)
  loglik <- sum(y*log(p)) + sum((1 - y)*log(1 - p))
  return(loglik)
}

# optimize
logit <- function(y, X) {
  init.par <- rep(0, ncol(X))