Exponential Families in Theory and Practice PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Exponential Families in Theory and Practice PDF full book. Access full book title Exponential Families in Theory and Practice by Bradley Efron. Download full books in PDF and EPUB format.
Author: Bradley Efron
Publisher: Cambridge University Press
ISBN: 1108805434
Category : Mathematics
Languages : en
Pages : 264
Get Book Here
Book 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.
Author: Bradley Efron
Publisher: Cambridge University Press
ISBN: 1108805434
Category : Mathematics
Languages : en
Pages : 264
Get Book Here
Book 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.
Author: Bradley Efron
Publisher: Cambridge University Press
ISBN: 1108488900
Category : Computers
Languages : en
Pages : 263
Get Book Here
Book Description
This accessible course on a central player in modern statistical practice connects models with methodology, without need for advanced math.
Author: Lawrence D. Brown
Publisher: IMS
ISBN: 9780940600102
Category : Business & Economics
Languages : en
Pages : 302
Get Book Here
Book Description
Author: Ole Barndorff- Nielsen
Publisher:
ISBN:
Category : Exponential functions
Languages : da
Pages :
Get Book Here
Book Description
Author: O. Barndorff-Nielsen
Publisher: John Wiley & Sons
ISBN: 1118857372
Category : Mathematics
Languages : en
Pages : 248
Get Book Here
Book Description
First published by Wiley in 1978, this book is being re-issued with a new Preface by the author. The roots of the book lie in the writings of RA Fisher both as concerns results and the general stance to statistical science, and this stance was the determining factor in the author's selection of topics. His treatise brings together results on aspects of statistical information, notably concerning likelihood functions, plausibility functions, ancillarity, and sufficiency, and on exponential families of probability distributions.
Author: Bo-Cheng Wei
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 248
Get Book Here
Book Description
This book gives a comprehensive introduction to exponential family nonlinear models, which are the natural extension of generalized linear models and normal nonlinear regression models. The differential geometric framework is presented for these models and geometric methods are widely used in this book. This book is ideally suited for researchers in statistical interfaces and graduate students with a basic knowledge of statistics.
Author: B. Jørgensen
Publisher:
ISBN:
Category :
Languages : en
Pages : 193
Get Book Here
Book Description
Author: Ole E. Barndorff-Nielsen
Publisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 268
Get Book Here
Book Description
Author: Bradley Efron
Publisher: Cambridge University Press
ISBN: 1139492136
Category : Mathematics
Languages : en
Pages :
Get Book Here
Book Description
We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.
Author: Jeff Gill
Publisher: SAGE Publications
ISBN: 1506320244
Category : Social Science
Languages : en
Pages : 135
Get Book Here
Book Description
The author explains the theoretical underpinnings of generalized linear models so that researchers can decide how to select the best way to adapt their data for this type of analysis. Examples are provided to illustrate the application of GLM to actual data and the author includes his Web address where additional resources can be found.
