Algebraic and Geometric Methods in Statistics

Algebraic and Geometric Methods in Statistics
Author :
Publisher : Cambridge University Press
Total Pages : 447
Release :
ISBN-10 : 9780521896191
ISBN-13 : 0521896193
Rating : 4/5 (91 Downloads)

Book Synopsis Algebraic and Geometric Methods in Statistics by : Paolo Gibilisco

Download or read book Algebraic and Geometric Methods in Statistics written by Paolo Gibilisco and published by Cambridge University Press. This book was released on 2010 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of algebraic statistics and information geometry, which also explores the emerging connections between these two disciplines.

Differential-Geometrical Methods in Statistics

Differential-Geometrical Methods in Statistics
Author :
Publisher : Springer Science & Business Media
Total Pages : 302
Release :
ISBN-10 : 9781461250562
ISBN-13 : 1461250560
Rating : 4/5 (62 Downloads)

Book Synopsis Differential-Geometrical Methods in Statistics by : Shun-ichi Amari

Download or read book Differential-Geometrical Methods in Statistics written by Shun-ichi Amari and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews: "In this Lecture Note volume the author describes his differential-geometric approach to parametrical statistical problems summarizing the results he had published in a series of papers in the last five years. The author provides a geometric framework for a special class of test and estimation procedures for curved exponential families. ... ... The material and ideas presented in this volume are important and it is recommended to everybody interested in the connection between statistics and geometry ..." #Metrika#1 "More than hundred references are given showing the growing interest in differential geometry with respect to statistics. The book can only strongly be recommended to a geodesist since it offers many new insights into statistics on a familiar ground." #Manuscripta Geodaetica#2

Geometric Methods in Algebra and Number Theory

Geometric Methods in Algebra and Number Theory
Author :
Publisher : Springer Science & Business Media
Total Pages : 365
Release :
ISBN-10 : 9780817644178
ISBN-13 : 0817644172
Rating : 4/5 (78 Downloads)

Book Synopsis Geometric Methods in Algebra and Number Theory by : Fedor Bogomolov

Download or read book Geometric Methods in Algebra and Number Theory written by Fedor Bogomolov and published by Springer Science & Business Media. This book was released on 2006-06-22 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: * Contains a selection of articles exploring geometric approaches to problems in algebra, algebraic geometry and number theory * The collection gives a representative sample of problems and most recent results in algebraic and arithmetic geometry * Text can serve as an intense introduction for graduate students and those wishing to pursue research in algebraic and arithmetic geometry

Algebraic and Geometric Ideas in the Theory of Discrete Optimization

Algebraic and Geometric Ideas in the Theory of Discrete Optimization
Author :
Publisher : SIAM
Total Pages : 320
Release :
ISBN-10 : 9781611972436
ISBN-13 : 1611972434
Rating : 4/5 (36 Downloads)

Book Synopsis Algebraic and Geometric Ideas in the Theory of Discrete Optimization by : Jesus A. De Loera

Download or read book Algebraic and Geometric Ideas in the Theory of Discrete Optimization written by Jesus A. De Loera and published by SIAM. This book was released on 2013-01-31 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, many new techniques have emerged in the mathematical theory of discrete optimization that have proven to be effective in solving a number of hard problems. This book presents these recent advances, particularly those that arise from algebraic geometry, commutative algebra, convex and discrete geometry, generating functions, and other tools normally considered outside of the standard curriculum in optimization. These new techniques, all of which are presented with minimal prerequisites, provide a transition from linear to nonlinear discrete optimization. This book can be used as a textbook for advanced undergraduates or first-year graduate students in mathematics, computer science or operations research. It is also appropriate for mathematicians, engineers, and scientists engaged in computation who wish to gain a deeper understanding of how and why algorithms work.

Algebraic Geometry and Statistical Learning Theory

Algebraic Geometry and Statistical Learning Theory
Author :
Publisher : Cambridge University Press
Total Pages : 295
Release :
ISBN-10 : 9780521864671
ISBN-13 : 0521864674
Rating : 4/5 (71 Downloads)

Book Synopsis Algebraic Geometry and Statistical Learning Theory by : Sumio Watanabe

Download or read book Algebraic Geometry and Statistical Learning Theory written by Sumio Watanabe and published by Cambridge University Press. This book was released on 2009-08-13 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sure to be influential, Watanabe's book lays the foundations for the use of algebraic geometry in statistical learning theory. Many models/machines are singular: mixture models, neural networks, HMMs, Bayesian networks, stochastic context-free grammars are major examples. The theory achieved here underpins accurate estimation techniques in the presence of singularities.

An Introduction to Algebraic Statistics with Tensors

An Introduction to Algebraic Statistics with Tensors
Author :
Publisher : Springer Nature
Total Pages : 240
Release :
ISBN-10 : 9783030246242
ISBN-13 : 3030246248
Rating : 4/5 (42 Downloads)

Book Synopsis An Introduction to Algebraic Statistics with Tensors by : Cristiano Bocci

Download or read book An Introduction to Algebraic Statistics with Tensors written by Cristiano Bocci and published by Springer Nature. This book was released on 2019-09-11 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to various aspects of Algebraic Statistics with the principal aim of supporting Master’s and PhD students who wish to explore the algebraic point of view regarding recent developments in Statistics. The focus is on the background needed to explore the connections among discrete random variables. The main objects that encode these relations are multilinear matrices, i.e., tensors. The book aims to settle the basis of the correspondence between properties of tensors and their translation in Algebraic Geometry. It is divided into three parts, on Algebraic Statistics, Multilinear Algebra, and Algebraic Geometry. The primary purpose is to describe a bridge between the three theories, so that results and problems in one theory find a natural translation to the others. This task requires, from the statistical point of view, a rather unusual, but algebraically natural, presentation of random variables and their main classical features. The third part of the book can be considered as a short, almost self-contained, introduction to the basic concepts of algebraic varieties, which are part of the fundamental background for all who work in Algebraic Statistics.

Algebraic Statistics for Computational Biology

Algebraic Statistics for Computational Biology
Author :
Publisher : Cambridge University Press
Total Pages : 440
Release :
ISBN-10 : 0521857007
ISBN-13 : 9780521857000
Rating : 4/5 (07 Downloads)

Book Synopsis Algebraic Statistics for Computational Biology by : L. Pachter

Download or read book Algebraic Statistics for Computational Biology written by L. Pachter and published by Cambridge University Press. This book was released on 2005-08-22 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, first published in 2005, offers an introduction to the application of algebraic statistics to computational biology.