Asymptotic statistics : with a view to stochastic processes / / Reinhard Höpfner

• Record Nr.: UNINA9910825196303321
• Autore: Höpfner R (Reinhard), <1955->
• Pubbl/distr/stampa: Berlin : , : Walter de Gruyter GmbH & Co. KG, , [2014]; ©2014
• ISBN: 3-11-036778-5; 3-11-025028-4
• Descrizione fisica: 1 online resource (286 p.)
• Collana: De Gruyter Textbook; De Gruyter textbook
• Classificazione: SK 820
• Disciplina: 519.6/23
• Soggetti: Mathematical statistics - Asymptotic theory; Asymptotic distribution (Probability theory)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Frontmatter -- Preface -- Contents -- Chapter 1 Score and Information -- Chapter 2 Minimum Distance Estimators -- Chapter 3 Contiguity -- Chapter 4 L2-differentiable Statistical Models -- Chapter 5 Gaussian Shift Models -- Chapter 6 Quadratic Experiments and Mixed Normal Experiments -- Chapter 7 Local Asymptotics of Type LAN, LAMN, LAQ -- Chapter 8 Some Stochastic Process Examples for Local Asymptotics of Type LAN, LAMN and LAQ -- Chapter 9 Appendix -- Bibliography -- Index
• Sommario/riassunto: This textbook is devoted to the general asymptotic theory of statistical experiments. Local asymptotics for statistical models in the sense of local asymptotic (mixed) normality or local asymptotic quadraticity make up the core of the book. Numerous examples deal with classical independent and identically distributed models and with stochastic processes. The book can be read in different ways, according to possibly different mathematical preferences of the reader. One reader may focus on the statistical theory, and thus on the chapters about Gaussian shift models, mixed normal and quadratic models, and on local asymptotics where the limit model is a Gaussian shift or a mixed normal or a quadratic experiment (LAN, LAMN, LAQ). Another reader ; may prefer an introduction to stochastic process models where given statistical results apply, and thus concentrate on subsections or chapters on likelihood ratio processes and some diffusion type models where LAN, LAMN or LAQ occurs. Finally, readers might put together both aspects. The book is suitable for graduate students starting to work in statistics of stochastic processes, as well as for researchers interested in a precise introduction to this area.