A Graduate Course on Statistical Inference (Springer Texts in Statistics)

has checkmarks in pencil on several chapters, the text is not obscured, Shows minor wear to the cover and pages. The binding is fully intact and secure. This is a good reading or studying copy and has been verified that all pages are legible. 100% satisfaction guaranteed! --- Part of the Springer Texts in Statistics series, this graduate textbook of theoretical statistics is organised around three principal themes: finite-sample theory, asymptotic theory, and Bayesian statistics. A chapter on estimating equations is included as a means of unifying methodologies such as generalized linear models, generalized estimating equations, quasi-likelihood estimation, and conditional inference, and a common set of regularity conditions and tools is applied throughout. The Bayesian material treats estimation, testing, and classification, developing the prior and posterior framework from Bayes' theorem. The authors suggest modular pathways through the material - for instance, Chapters 1, 3, 4, 7, 10, and 11 for an advanced course on hypothesis testing, or Chapters 1, 2, 5, part of 6, 7, 8, and 9 for a course on point estimation and Bayesian statistics, supporting use over one or two semesters. The text grew from lecture notes for two graduate courses taught at the Pennsylvania State University. Exercise sets are provided. …