Author :
Publisher : American Mathematical Soc.
Page : 340 pages
File Size : 39,97 MB
Release : 2001
Category : Algebra
ISBN : 9780821856239
[PDF] Algebraic Methods In Statistics And Probability eBook
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Algebraic Methods in Statistics and Probability II
Marlos A. G. Viana
Author : Marlos A. G. Viana
Publisher : American Mathematical Soc.
Page : 358 pages
File Size : 29,97 MB
Release : 2010
Category : Mathematics
ISBN : 0821848917
A decade after the publication of Contemporary Mathematics Vol. 287, the present volume demonstrates the consolidation of important areas, such as algebraic statistics, computational commutative algebra, and deeper aspects of graphical models. --
Algebraic Methods in Statistics and Probability
Marlos A. G. Viana
Author : Marlos A. G. Viana
Publisher : American Mathematical Soc.
Page : 354 pages
File Size : 41,72 MB
Release : 2001
Category : Mathematics
ISBN : 0821826875
The 23 papers report recent developments in using the technique to help clarify the relationship between phenomena and data in a number of natural and social sciences. Among the topics are a coordinate-free approach to multivariate exponential families, some rank-based hypothesis tests for covariance structure and conditional independence, deconvolution density estimation on compact Lie groups, random walks on regular languages and algebraic systems of generating functions, and the extendibility of statistical models. There is no index. c. Book News Inc.
Algebraic and Geometric Methods in Statistics
Paolo Gibilisco
Author : Paolo Gibilisco
Publisher : Cambridge University Press
Page : 447 pages
File Size : 26,3 MB
Release : 2010
Category : Mathematics
ISBN : 0521896193
An up-to-date account of algebraic statistics and information geometry, which also explores the emerging connections between these two disciplines.
Lectures on Algebraic Statistics
Mathias Drton
Author : Mathias Drton
Publisher : Springer Science & Business Media
Page : 177 pages
File Size : 26,61 MB
Release : 2009-04-25
Category : Mathematics
ISBN : 3764389052
How does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of "algebraic statistics". In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models.
Algebraic Statistics
Seth Sullivant
Author : Seth Sullivant
Publisher : American Mathematical Soc.
Page : 490 pages
File Size : 16,61 MB
Release : 2018-11-19
Category : Geometry, Algebraic
ISBN : 1470435179
Algebraic statistics uses tools from algebraic geometry, commutative algebra, combinatorics, and their computational sides to address problems in statistics and its applications. The starting point for this connection is the observation that many statistical models are semialgebraic sets. The algebra/statistics connection is now over twenty years old, and this book presents the first broad introductory treatment of the subject. Along with background material in probability, algebra, and statistics, this book covers a range of topics in algebraic statistics including algebraic exponential families, likelihood inference, Fisher's exact test, bounds on entries of contingency tables, design of experiments, identifiability of hidden variable models, phylogenetic models, and model selection. With numerous examples, references, and over 150 exercises, this book is suitable for both classroom use and independent study.
Algebraic Statistics for Computational Biology
L. Pachter
Author : L. Pachter
Publisher : Cambridge University Press
Page : 440 pages
File Size : 15,91 MB
Release : 2005-08-22
Category : Mathematics
ISBN : 9780521857000
This book, first published in 2005, offers an introduction to the application of algebraic statistics to computational biology.
Methods of Mathematics Applied to Calculus, Probability, and Statistics
Richard W. Hamming
Author : Richard W. Hamming
Publisher : Courier Corporation
Page : 882 pages
File Size : 31,64 MB
Release : 2012-06-28
Category : Mathematics
ISBN : 0486138879
This 4-part treatment begins with algebra and analytic geometry and proceeds to an exploration of the calculus of algebraic functions and transcendental functions and applications. 1985 edition. Includes 310 figures and 18 tables.
Random Walks in the Quarter-Plane
Guy Fayolle
Author : Guy Fayolle
Publisher : Springer Science & Business Media
Page : 169 pages
File Size : 48,10 MB
Release : 2012-12-06
Category : Mathematics
ISBN : 3642600018
Promoting original mathematical methods to determine the invariant measure of two-dimensional random walks in domains with boundaries, the authors use Using Riemann surfaces and boundary value problems to propose completely new approaches to solve functional equations of two complex variables. These methods can also be employed to characterize the transient behavior of random walks in the quarter plane.
Algebraic and Discrete Mathematical Methods for Modern Biology
Raina Robeva
Author : Raina Robeva
Publisher : Academic Press
Page : 383 pages
File Size : 50,15 MB
Release : 2015-05-09
Category : Mathematics
ISBN : 0128012714
Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems. Each chapter begins with a question from modern biology, followed by the description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set. This book is appropriate for mathematics courses such as finite mathematics, discrete structures, linear algebra, abstract/modern algebra, graph theory, probability, bioinformatics, statistics, biostatistics, and modeling, as well as for biology courses such as genetics, cell and molecular biology, biochemistry, ecology, and evolution. Examines significant questions in modern biology and their mathematical treatments Presents important mathematical concepts and tools in the context of essential biology Features material of interest to students in both mathematics and biology Presents chapters in modular format so coverage need not follow the Table of Contents Introduces projects appropriate for undergraduate research Utilizes freely accessible software for visualization, simulation, and analysis in modern biology Requires no calculus as a prerequisite Provides a complete Solutions Manual Features a companion website with supplementary resources