Theory of Inference for DS

Catalog description

Theory of Inference for Data Science: Theory of estimation and sufficiency including maximum likelihood and minimum variance estimation suitable for large throughput data; Neyman-Pearson theory of testing hypotheses; elements of decision theory; Asymptotic results for large scale estimation and testing based on likelihoods, general estimating equations, empirical Bayesian estimation and resampling plans.