Binding: Paperback
Description: During the past half - century exponential families have attained a position at the center of parametric statistical inference. Theoretical advances have been matched and more than matched in the world of applications where logistic regression by itself has become the go - to methodology in medical statistics computer - based prediction algorithms and the social sciences. This book is based on a one - semester graduate course for first year Ph. D. and advanced master's students. After presenting the basic structure of univariate and multivariate exponential families their application to generalized linear models including logistic and Poisson regression is described in detail emphasizing geometrical ideas computational practice and the analogy with ordinary linear regression. Connections are made with a variety of current statistical methodologies: missing data survival analysis and proportional hazards false discovery rates bootstrapping and empirical Bayes analysis. The book connects exponential family theory with its applications in a way that doesn't require advanced mathematical preparation.
Title: Exponential Families In Theory And Practice
Author(s): Efron Bradley (Stanford University California)
Publisher: Cambridge University Press
Barcode: 9781108715669
Pages: 262 Pages, Worked Examples Or Exercises
Publication Date: 2/9/2023
Series: Institute of Mathematical Statistics Textbooks
Category: Machine Learning