Statistical Inference II

4.0 credits

Types of convergence; asymptotic linearity; influence functions; consistency and asymptotic normality; large sample estimation, maximum likelihood estimation; Wald, likelihood ratio, and score tests; generalized Neyman-Pearson lemma; nuisance parameters; efficiency; alternative methods for estimation (M-estimation, GEE, generalized method of moments); resampling methods (bootstrap, permutation tests); decision-theoretic inference.