: Classical and Bayesian estimation problems, focusing on uniformly minimum variance unbiased estimators (UMVUE) . Key Topics : Data Summarization and Sufficiency Unbiased Estimation and Information Inequality Asymptotic Theory (Consistency, CAN, BAN) Bayes and Minimax Estimation Confidence Interval Estimation Length : ~808 pages (Physical); ~1006 pages (Kindle). Statistical Inference: Testing of Hypotheses Co-authored with Namita Srivastava (2009).
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: The book provides explicit clarifications for complex steps in theorem proofs, making it more accessible than standard theoretical texts . : Classical and Bayesian estimation problems, focusing on
: Provides rigorous developments on Most Powerful (MP), Uniformly Most Powerful (UMP), and UMP unbiased tests PHI Learning Non-Parametric Analysis If you absolutely cannot afford Srivastava’s book, here
: This branch deals with making decisions about a population based on sample data.