Algebraic Methods in Statistics and Probability

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Author :
Publisher : American Mathematical Soc.
ISBN 13 : 9780821856239
Total Pages : 340 pages
Book Rating : 4.8/5 (562 download)

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Book Synopsis Algebraic Methods in Statistics and Probability by :

Download or read book Algebraic Methods in Statistics and Probability written by and published by American Mathematical Soc.. This book was released on 2001 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Algebraic Methods in Statistics and Probability II

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Author :
Publisher : American Mathematical Soc.
ISBN 13 : 0821848917
Total Pages : 358 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Algebraic Methods in Statistics and Probability II by : Marlos A. G. Viana

Download or read book Algebraic Methods in Statistics and Probability II written by Marlos A. G. Viana and published by American Mathematical Soc.. This book was released on 2010 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Author :
Publisher : American Mathematical Soc.
ISBN 13 : 0821826875
Total Pages : 354 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Algebraic Methods in Statistics and Probability by : Marlos A. G. Viana

Download or read book Algebraic Methods in Statistics and Probability written by Marlos A. G. Viana and published by American Mathematical Soc.. This book was released on 2001 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : Cambridge University Press
ISBN 13 : 0521896193
Total Pages : 447 pages
Book Rating : 4.5/5 (218 download)

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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.

Lectures on Algebraic Statistics

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Publisher : Springer Science & Business Media
ISBN 13 : 3764389052
Total Pages : 172 pages
Book Rating : 4.7/5 (643 download)

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Book Synopsis Lectures on Algebraic Statistics by : Mathias Drton

Download or read book Lectures on Algebraic Statistics written by Mathias Drton and published by Springer Science & Business Media. This book was released on 2009-04-25 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : CRC Press
ISBN 13 : 1420035762
Total Pages : 180 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Algebraic Statistics by : Giovanni Pistone

Download or read book Algebraic Statistics written by Giovanni Pistone and published by CRC Press. This book was released on 2000-12-21 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. It begins with an introduction to Grobner bases and a thorough description of their applications to experimental design. A special chapter covers the binary case

Algebraic Statistics for Computational Biology

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Publisher : Cambridge University Press
ISBN 13 : 9780521857000
Total Pages : 440 pages
Book Rating : 4.8/5 (57 download)

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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.

Algebraic Statistics

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Publisher : American Mathematical Society
ISBN 13 : 1470475103
Total Pages : 506 pages
Book Rating : 4.4/5 (74 download)

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Book Synopsis Algebraic Statistics by : Seth Sullivant

Download or read book Algebraic Statistics written by Seth Sullivant and published by American Mathematical Society. This book was released on 2023-11-17 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Methods of Mathematics Applied to Calculus, Probability, and Statistics

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Publisher : Courier Corporation
ISBN 13 : 0486138879
Total Pages : 882 pages
Book Rating : 4.4/5 (861 download)

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Book Synopsis Methods of Mathematics Applied to Calculus, Probability, and Statistics by : Richard W. Hamming

Download or read book Methods of Mathematics Applied to Calculus, Probability, and Statistics written by Richard W. Hamming and published by Courier Corporation. This book was released on 2012-06-28 with total page 882 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : Springer Science & Business Media
ISBN 13 : 3642600018
Total Pages : 169 pages
Book Rating : 4.6/5 (426 download)

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Book Synopsis Random Walks in the Quarter-Plane by : Guy Fayolle

Download or read book Random Walks in the Quarter-Plane written by Guy Fayolle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Understanding Advanced Statistical Methods

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Publisher : CRC Press
ISBN 13 : 1466512113
Total Pages : 572 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Understanding Advanced Statistical Methods by : Peter Westfall

Download or read book Understanding Advanced Statistical Methods written by Peter Westfall and published by CRC Press. This book was released on 2013-04-09 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian me

Algebraic and Discrete Mathematical Methods for Modern Biology

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Publisher : Academic Press
ISBN 13 : 0128012714
Total Pages : 382 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Algebraic and Discrete Mathematical Methods for Modern Biology by : Raina Robeva

Download or read book Algebraic and Discrete Mathematical Methods for Modern Biology written by Raina Robeva and published by Academic Press. This book was released on 2015-05-09 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Algebraic Geometry and Statistical Learning Theory

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Publisher : Cambridge University Press
ISBN 13 : 0521864674
Total Pages : 295 pages
Book Rating : 4.5/5 (218 download)

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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.

Methods of Mathematics Applied to Calculus, Probability, and Statistics

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Publisher :
ISBN 13 : 9781621986058
Total Pages : 857 pages
Book Rating : 4.9/5 (86 download)

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Book Synopsis Methods of Mathematics Applied to Calculus, Probability, and Statistics by : Richard Wesley Hamming

Download or read book Methods of Mathematics Applied to Calculus, Probability, and Statistics written by Richard Wesley Hamming and published by . This book was released on 1985 with total page 857 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text focuses on the most widely used applications of mathematical methods, including those related to probability and statistics. The 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.

Basics of Matrix Algebra for Statistics with R

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Publisher : CRC Press
ISBN 13 : 1315360055
Total Pages : 159 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Basics of Matrix Algebra for Statistics with R by : Nick Fieller

Download or read book Basics of Matrix Algebra for Statistics with R written by Nick Fieller and published by CRC Press. This book was released on 2018-09-03 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Thorough Guide to Elementary Matrix Algebra and Implementation in R Basics of Matrix Algebra for Statistics with R provides a guide to elementary matrix algebra sufficient for undertaking specialized courses, such as multivariate data analysis and linear models. It also covers advanced topics, such as generalized inverses of singular and rectangular matrices and manipulation of partitioned matrices, for those who want to delve deeper into the subject. The book introduces the definition of a matrix and the basic rules of addition, subtraction, multiplication, and inversion. Later topics include determinants, calculation of eigenvectors and eigenvalues, and differentiation of linear and quadratic forms with respect to vectors. The text explores how these concepts arise in statistical techniques, including principal component analysis, canonical correlation analysis, and linear modeling. In addition to the algebraic manipulation of matrices, the book presents numerical examples that illustrate how to perform calculations by hand and using R. Many theoretical and numerical exercises of varying levels of difficulty aid readers in assessing their knowledge of the material. Outline solutions at the back of the book enable readers to verify the techniques required and obtain numerical answers. Avoiding vector spaces and other advanced mathematics, this book shows how to manipulate matrices and perform numerical calculations in R. It prepares readers for higher-level and specialized studies in statistics.

Probability and Statistics

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Publisher : Macmillan
ISBN 13 : 9780716747420
Total Pages : 704 pages
Book Rating : 4.7/5 (474 download)

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Book Synopsis Probability and Statistics by : Michael J. Evans

Download or read book Probability and Statistics written by Michael J. Evans and published by Macmillan. This book was released on 2004 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.

Statistics in the Public Interest

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Publisher : Springer Nature
ISBN 13 : 303075460X
Total Pages : 574 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Statistics in the Public Interest by : Alicia L. Carriquiry

Download or read book Statistics in the Public Interest written by Alicia L. Carriquiry and published by Springer Nature. This book was released on 2022-04-22 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume surveys a variety of topics in statistics and the social sciences in memory of the late Stephen Fienberg. The book collects submissions from a wide range of contemporary authors to explore the fields in which Fienberg made significant contributions, including contingency tables and log-linear models, privacy and confidentiality, forensics and the law, the decennial census and other surveys, the National Academies, Bayesian theory and methods, causal inference and causes of effects, mixed membership models, and computing and machine learning. Each section begins with an overview of Fienberg’s contributions and continues with chapters by Fienberg’s students, colleagues, and collaborators exploring recent advances and the current state of research on the topic. In addition, this volume includes a biographical introduction as well as a memorial concluding chapter comprised of entries from Stephen and Joyce Fienberg’s close friends, former students, colleagues, and other loved ones, as well as a photographic tribute.