Information And Exponential Families PDF Download
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Author | : O. Barndorff-Nielsen |
Publisher | : John Wiley & Sons |
Total Pages | : 248 |
Release | : 2014-05-07 |
Genre | : Mathematics |
ISBN | : 1118857372 |
Download Information and Exponential Families Book in PDF, ePub and Kindle
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 | : Ole E. Barndorff-Nielsen |
Publisher | : |
Total Pages | : 238 |
Release | : 1978 |
Genre | : Distribution (Probability theory) |
ISBN | : |
Download Information and Exponential Families Book in PDF, ePub and Kindle
Author | : Ole Barndorff-Nielsen |
Publisher | : |
Total Pages | : 238 |
Release | : 1978 |
Genre | : |
ISBN | : 9780835733915 |
Download Information and Exponential Families Book in PDF, ePub and Kindle
Author | : Uwe Küchler |
Publisher | : Springer Science & Business Media |
Total Pages | : 325 |
Release | : 2006-05-09 |
Genre | : Mathematics |
ISBN | : 0387227652 |
Download Exponential Families of Stochastic Processes Book in PDF, ePub and Kindle
A comprehensive account of the statistical theory of exponential families of stochastic processes. The book reviews the progress in the field made over the last ten years or so by the authors - two of the leading experts in the field - and several other researchers. The theory is applied to a broad spectrum of examples, covering a large number of frequently applied stochastic process models with discrete as well as continuous time. To make the reading even easier for statisticians with only a basic background in the theory of stochastic process, the first part of the book is based on classical theory of stochastic processes only, while stochastic calculus is used later. Most of the concepts and tools from stochastic calculus needed when working with inference for stochastic processes are introduced and explained without proof in an appendix. This appendix can also be used independently as an introduction to stochastic calculus for statisticians. Numerous exercises are also included.
Author | : Lawrence D. Brown |
Publisher | : IMS |
Total Pages | : 302 |
Release | : 1986 |
Genre | : Business & Economics |
ISBN | : 9780940600102 |
Download Fundamentals of Statistical Exponential Families Book in PDF, ePub and Kindle
Author | : Stefan Bedbur |
Publisher | : Springer Nature |
Total Pages | : 147 |
Release | : 2021-10-07 |
Genre | : Mathematics |
ISBN | : 3030819000 |
Download Multivariate Exponential Families: A Concise Guide to Statistical Inference Book in PDF, ePub and Kindle
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.
Author | : Bradley Efron |
Publisher | : Cambridge University Press |
Total Pages | : 264 |
Release | : 2022-12-15 |
Genre | : Mathematics |
ISBN | : 1108805434 |
Download Exponential Families in Theory and Practice Book in PDF, ePub and Kindle
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 | : Rolf Sundberg |
Publisher | : Cambridge University Press |
Total Pages | : 297 |
Release | : 2019-08-29 |
Genre | : Business & Economics |
ISBN | : 1108476597 |
Download Statistical Modelling by Exponential Families Book in PDF, ePub and Kindle
A readable, digestible introduction to essential theory and wealth of applications, with a vast set of examples and numerous exercises.
Author | : Martin J. Wainwright |
Publisher | : Now Publishers Inc |
Total Pages | : 324 |
Release | : 2008 |
Genre | : Computers |
ISBN | : 1601981848 |
Download Graphical Models, Exponential Families, and Variational Inference Book in PDF, ePub and Kindle
The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.
Author | : Frank Nielsen |
Publisher | : Springer Nature |
Total Pages | : 929 |
Release | : 2021-07-14 |
Genre | : Computers |
ISBN | : 3030802094 |
Download Geometric Science of Information Book in PDF, ePub and Kindle
This book constitutes the proceedings of the 5th International Conference on Geometric Science of Information, GSI 2021, held in Paris, France, in July 2021. The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: Probability and statistics on Riemannian Manifolds; sub-Riemannian geometry and neuromathematics; shapes spaces; geometry of quantum states; geometric and structure preserving discretizations; information geometry in physics; Lie group machine learning; geometric and symplectic methods for hydrodynamical models; harmonic analysis on Lie groups; statistical manifold and Hessian information geometry; geometric mechanics; deformed entropy, cross-entropy, and relative entropy; transformation information geometry; statistics, information and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimization; divergence statistics; optimal transport and learning; and geometric structures in thermodynamics and statistical physics.