Multivariate Exponential Families: A Concise Guide to Statistical Inference
Author | : Stefan Bedbur |
Publisher | : Springer Nature |
Total Pages | : 147 |
Release | : 2021-10-07 |
ISBN-13 | : 9783030819002 |
ISBN-10 | : 3030819000 |
Rating | : 4/5 (00 Downloads) |
Download or read book Multivariate Exponential Families: A Concise Guide to Statistical Inference written by Stefan Bedbur and published by Springer Nature. This book was released on 2021-10-07 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.