Multivariate Exponential Families: A Concise Guide to Statistical Inference (Paperback, 1st ed. 2021)

This book provides a concise introduction to exponential families. Parametric families of probability distributions and their properties are extensively studied in the literature on statistical modeling and inference. Exponential families of distributions comprise density functions of a particular form, which enables general assertions and leads to nice features. With a focus on parameter estimation and hypotheses testing, the text introduces the reader to distributional and statistical properties of multivariate and multiparameter exponential families along with a variety of detailed examples. The material is widely self-contained and written in a mathematical setting. It may serve both as a concise, mathematically rigorous course on exponential families in a systematic structure and as an introduction to Mathematical Statistics restricted to the use of exponential families.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Statistics
Release date:	October 2021
First published:	2021
Authors:	Stefan Bedbur • Udo Kamps
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	142
Edition:	1st ed. 2021
ISBN-13:	978-3-03-081899-9
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
LSN:	3-03-081899-3
Barcode:	9783030818999

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