Mathematical Statistics

Discover the essential concepts of statistical theory in "Mathematical Statistics" by Peter J. Bickel, published in 2015. This comprehensive text spans 576 pages and is ideal for doctorate-level study. The second edition delves into fundamental statistical principles, including estimation, prediction, hypothesis testing, confidence sets, and Bayesian analysis, while emphasizing the decision theory framework.

Bickel's approach provides rigorous proofs of significant results, clearly demonstrating how these theories apply to practical methods in statistical analysis. The book begins with an exploration of non- and semiparametric models, transitioning into a detailed examination of parametric models and maximum likelihood estimates (MLEs). Whether you are a student or a seasoned statistician, this volume is a pivotal resource for mastering the intricacies of mathematical statistics. Enhance your statistical knowledge with this authoritative guide by one of the leading figures in statistical education.