A Graduate Course on Statistical Inference

• Κύριοι συγγραφείς: Li, Bing (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Babu, G. Jogesh (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Springer Texts in Statistics,
• Θέματα: Statistics .; Statistical Theory and Methods.
• Φυσική περιγραφή: XII, 379 p. 148 illus. online resource.
• ISBN: 9781493997619
• ISSN: 1431-875X
• DOI: 10.1007/978-1-4939-9761-9

This textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The authors have included a chapter on estimating equations as a means to unify a range of useful methodologies, including generalized linear models, generalized estimation equations, quasi-likelihood estimation, and conditional inference. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course.