Covers Generalized Linear Models, likelihood, deviance, link functions, sampling methods, Poisson regression, over-dispersion, and alternative regression models.
Explores variance reduction techniques in stochastic simulation, emphasizing the use of auxiliary random variables and sample averages to improve efficiency.
