Markov Bases In Algebraic Statistics
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Markov Bases In Algebraic Statistics
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Author : Satoshi Aoki
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-25
Markov Bases In Algebraic Statistics written by Satoshi Aoki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-25 with Mathematics categories.
Algebraic statistics is a rapidly developing field, where ideas from statistics and algebra meet and stimulate new research directions. One of the origins of algebraic statistics is the work by Diaconis and Sturmfels in 1998 on the use of Gröbner bases for constructing a connected Markov chain for performing conditional tests of a discrete exponential family. In this book we take up this topic and present a detailed summary of developments following the seminal work of Diaconis and Sturmfels. This book is intended for statisticians with minimal backgrounds in algebra. As we ourselves learned algebraic notions through working on statistical problems and collaborating with notable algebraists, we hope that this book with many practical statistical problems is useful for statisticians to start working on the field.
Lectures On Algebraic Statistics
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Author : Mathias Drton
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-10
Lectures On Algebraic Statistics written by Mathias Drton and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-10 with Mathematics categories.
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 Methods In Statistics And Probability Ii
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Author : Marlos A. G. Viana
language : en
Publisher: American Mathematical Soc.
Release Date : 2010
Algebraic Methods In Statistics And Probability Ii written by Marlos A. G. Viana and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
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 Statistics
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Author : Karl-Heinz Zimmermann
language : en
Publisher:
Release Date : 2015
Algebraic Statistics written by Karl-Heinz Zimmermann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Algebraic statistics brings together ideas from algebraic geometry, commutative algebra, and combinatorics to address problems in statistics and its applications. Computer algebra provides powerful tools for the study of algorithms and software. However, these tools are rarely prepared to address statistical challenges and therefore new algebraic results need often be developed. This way of interplay between algebra and statistics fertilizes both disciplines. Algebraic statistics is a relatively new branch of mathematics that developed and changed rapidly over the last ten years. The seminal work in this field was the paper of Diaconis and Sturmfels (1998) introducing the notion of Markov bases for toric statistical models and showing the connection to commutative algebra. Later on, the connection between algebra and statistics spread to a number of different areas including parametric inference, phylogenetic invariants, and algebraic tools for maximum likelihood estimation. These connection were highlighted in the celebrated book Algebraic Statistics for Computational Biology of Pachter and Sturmfels (2005) and subsequent publications. In this report, statistical models for discrete data are viewed as solutions of systems of polynomial equations. This allows to treat statistical models for sequence alignment, hidden Markov models, and phylogenetic tree models. These models are connected in the sense that if they are interpreted in the tropical algebra, the famous dynamic programming algorithms (Needleman-Wunsch, Viterbi, and Felsenstein) occur in a natural manner. More generally, if the models are interpreted in a higher dimensional analogue of the tropical algebra, the polytope algebra, parametric versions of these dynamic programming algorithms can be established. Markov bases allow to sample data in a given fibre using Markov chain Monte Carlo algorithms. In this way, Markov bases provide a means to increase the sample size and make statistical tests in inferential statistics more reliable. We will calculate Markov bases using Groebner bases in commutative polynomial rings. The manuscript grew out of lectures on algebraic statistics held for Master students of Computer Science at the Hamburg University of Technology. It appears that the first lecture held in the summer term 2008 was the first course of this kind in Germany. The current manuscript is the basis of a four-hour introductory course. The use of computer algebra systems is at the heart of the course. Maple is employed for symbolic computations, Singular for algebraic computations, and R for statistical computations. The second edition at hand is just a streamlined version of the first one.$cen$dAbstract
Gr Bner Bases
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Author : Takayuki Hibi
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-07
Gr Bner Bases written by Takayuki Hibi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-07 with Mathematics categories.
The idea of the Gröbner basis first appeared in a 1927 paper by F. S. Macaulay, who succeeded in creating a combinatorial characterization of the Hilbert functions of homogeneous ideals of the polynomial ring. Later, the modern definition of the Gröbner basis was independently introduced by Heisuke Hironaka in 1964 and Bruno Buchberger in 1965. However, after the discovery of the notion of the Gröbner basis by Hironaka and Buchberger, it was not actively pursued for 20 years. A breakthrough was made in the mid-1980s by David Bayer and Michael Stillman, who created the Macaulay computer algebra system with the help of the Gröbner basis. Since then, rapid development on the Gröbner basis has been achieved by many researchers, including Bernd Sturmfels. This book serves as a standard bible of the Gröbner basis, for which the harmony of theory, application, and computation are indispensable. It provides all the fundamentals for graduate students to learn the ABC’s of the Gröbner basis, requiring no special knowledge to understand those basic points. Starting from the introductory performance of the Gröbner basis (Chapter 1), a trip around mathematical software follows (Chapter 2). Then comes a deep discussion of how to compute the Gröbner basis (Chapter 3). These three chapters may be regarded as the first act of a mathematical play. The second act opens with topics on algebraic statistics (Chapter 4), a fascinating research area where the Gröbner basis of a toric ideal is a fundamental tool of the Markov chain Monte Carlo method. Moreover, the Gröbner basis of a toric ideal has had a great influence on the study of convex polytopes (Chapter 5). In addition, the Gröbner basis of the ring of differential operators gives effective algorithms on holonomic functions (Chapter 6). The third act (Chapter 7) is a collection of concrete examples and problems for Chapters 4, 5 and 6 emphasizing computation by using various software systems.
Lectures On Algebraic Statistics
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Author : Mathias Drton
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-25
Lectures On Algebraic Statistics written by Mathias Drton and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-25 with Mathematics categories.
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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Author : Seth Sullivant
language : en
Publisher: American Mathematical Society
Release Date : 2023-11-17
Algebraic Statistics written by Seth Sullivant and has been published by American Mathematical Society this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-17 with Mathematics categories.
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.
Two Algebraic Byways From Differential Equations Gr Bner Bases And Quivers
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Author : Kenji Iohara
language : en
Publisher: Springer Nature
Release Date : 2020-02-20
Two Algebraic Byways From Differential Equations Gr Bner Bases And Quivers written by Kenji Iohara and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-20 with Mathematics categories.
This edited volume presents a fascinating collection of lecture notes focusing on differential equations from two viewpoints: formal calculus (through the theory of Gröbner bases) and geometry (via quiver theory). Gröbner bases serve as effective models for computation in algebras of various types. Although the theory of Gröbner bases was developed in the second half of the 20th century, many works on computational methods in algebra were published well before the introduction of the modern algebraic language. Since then, new algorithms have been developed and the theory itself has greatly expanded. In comparison, diagrammatic methods in representation theory are relatively new, with the quiver varieties only being introduced – with big impact – in the 1990s. Divided into two parts, the book first discusses the theory of Gröbner bases in their commutative and noncommutative contexts, with a focus on algorithmic aspects and applications of Gröbner bases to analysis on systems of partial differential equations, effective analysis on rings of differential operators, and homological algebra. It then introduces representations of quivers, quiver varieties and their applications to the moduli spaces of meromorphic connections on the complex projective line. While no particular reader background is assumed, the book is intended for graduate students in mathematics, engineering and related fields, as well as researchers and scholars.
Algebraic And Geometric Methods In Discrete Mathematics
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Author : Heather A. Harrington
language : en
Publisher: American Mathematical Soc.
Release Date : 2017-03-16
Algebraic And Geometric Methods In Discrete Mathematics written by Heather A. Harrington and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-16 with Mathematics categories.
This volume contains the proceedings of the AMS Special Session on Algebraic and Geometric Methods in Applied Discrete Mathematics, held on January 11, 2015, in San Antonio, Texas. The papers present connections between techniques from “pure” mathematics and various applications amenable to the analysis of discrete models, encompassing applications of combinatorics, topology, algebra, geometry, optimization, and representation theory. Papers not only present novel results, but also survey the current state of knowledge of important topics in applied discrete mathematics. Particular highlights include: a new computational framework, based on geometric combinatorics, for structure prediction from RNA sequences; a new method for approximating the optimal solution of a sum of squares problem; a survey of recent Helly-type geometric theorems; applications of representation theory to voting theory and game theory; a study of fixed points of tensors; and exponential random graph models from the perspective of algebraic statistics with applications to networks. This volume was written for those trained in areas such as algebra, topology, geometry, and combinatorics who are interested in tackling problems in fields such as biology, the social sciences, data analysis, and optimization. It may be useful not only for experts, but also for students who wish to gain an applied or interdisciplinary perspective.
Algebraic And Geometric Methods In Statistics
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Author : Paolo Gibilisco
language : en
Publisher: Cambridge University Press
Release Date : 2010
Algebraic And Geometric Methods In Statistics written by Paolo Gibilisco and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.
An up-to-date account of algebraic statistics and information geometry, which also explores the emerging connections between these two disciplines.