Last edited by Fenrigor
Saturday, May 2, 2020 | History

7 edition of Algebraic Statistics found in the catalog.

Algebraic Statistics

Computational Commutative Algebra in Statistics (Monographs on Statistics and Applied Probability)

by Giovanni Pistone

  • 274 Want to read
  • 37 Currently reading

Published by Chapman & Hall/CRC .
Written in English

    Subjects:
  • Algebra,
  • Probability & statistics,
  • Mathematics,
  • Science/Mathematics,
  • Probability & Statistics - General,
  • Algebra - General,
  • General,
  • Mathematics / Probability & Statistics / Bayesian Analysis,
  • Mathematical Statistics

  • The Physical Object
    FormatHardcover
    Number of Pages160
    ID Numbers
    Open LibraryOL8795242M
    ISBN 101584882042
    ISBN 109781584882046

      "Easy Algebra Step-by-Step " teaches algebra in the form of a fantasy novel. The story's characters solve problems by using algebra. Readers discover the hows and whys of equations, negative numbers, exponents, roots and real numbers, algebraic expressions, functions, graphs, quadratic equations, polynomials, permutations and combinations, matrices and determinants, mathematical . Book Description 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 Gröbner bases and a thorough description of .

    Introductory Statistics follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text. 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.

    Another milestone was the workshop on Computational Algebraic Statistics which was held at the American Institute for Mathematics (AIM) at Palo Alto in December That workshop was built on the algebraic statistics paradigm, which is that statistical models for discrete data can be represented as solutions to systems of polynomial equations.   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.


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Algebraic Statistics by Giovanni Pistone Download PDF EPUB FB2

Algebraic Statistics (Graduate Studies in Mathematics) Hardcover – Novem Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device by: The models of algebraic statistics include those that are very familiar to researchers in genomic sequence analysis, namely hidden Markov models and graphical models.

This reviewer only read the first three chapters of this book, and so the following commentary will be restricted to these/5(3). 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 Gröbner bases and a thorough description of their applications to experimental by: DOI link for Algebraic Statistics.

Algebraic Statistics book. Computational Commutative Algebra in Statistics. By Giovanni Pistone, Eva Riccomagno, Henry P. Wynn. Edition 1st Edition. First Published eBook Published 21 December Pub. location New York. Imprint Chapman and Hall/CRC.

Algebraic Statistics Author: Seth Sullivant Publisher: American Mathematical Soc. ISBN: Category: Geometry, Algebraic Page: View: This book provides an introduction to various aspects of Algebraic Statistics and describes a bridge between the theories of Algebraic Statistics, Multilinear Algebra, and Algebraic Geometry, so that results and problems in one theory find a natural translation to the others.

Introduces the relatively new field of Algebraic Statistics. Includes exercises and open problems that complement the material and stimulate further research.

see more benefits. Buy this book. eB99 €. price for Spain (gross) Buy eBook. ISBN Digitally watermarked, DRM-free. In this algebraic framework, the parameters of the model as interpreted in statistics are functions of any form with the restriction that they belong to a specified field.

For example, Q(θ1, θp) is the set of all rational functions in θ1, θp with rational coefficients. The term algebraic statistics was coined in the book by Pistone et al., which primarily addresses experimental design. Algebraic statistics brings together ideas from algebraic geometry, commutative algebra, and combina-torics 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. Algebraic statistics is a relatively new field that has developed and changed rather rapidly over the last fifteen years. One of the first pieces of work in this area.

A Handbook of Statistics. Introduction to Vectors. Decision-Making using Financial Ratios. Statistics for Business and Economics. Understanding Statistics. An Introduction to Matlab. A Refresher Course in Mathematics. Introduction to statistical data analysis with R.

Elementary Linear Algebra: Part I. Introduction to Probability. Matrix Algebra. 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.

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. Books Advanced Search New Releases Best Sellers & More Children's Books Textbooks Textbook Rentals Best Books of the Month Probability & Statistics of o results for Books: Science & Math: Mathematics: Applied: Probability & Statistics.

In many introductory level courses today, teachers are challenged with the task of fitting in all of the core concepts of the course in a limited period of time. The Introductory Statistics teacher is no stranger to this challenge. To add to the difficulty, many textbooks contain an overabundance of material, which not only results in the need for further streamlining, but also in intimidated 4/5(8).

The book certainly achieves the authors’ stated aims of encouraging ‘dialogue between algebra and statistics, to benefit both disciplines.’ the book particularly effective as a tool for a reading group on algebraic statistics; it is an excellent resource, cuts straight to the subject’s open questions, and should be an interesting read for any researcher of theoretical statistics.” (Robin J.

Evans, SIAM Review, Manufacturer: Birkhäuser. Book Description. 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 Gröbner bases and a thorough description of their applications to experimental design. 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 on the use of Gröbner bases for constructing a connected Markov chain for performing conditional tests of a discrete exponential family.

I took a course in Algebraic Statistics from the book of Drton, Sturmfels, and Sullivant called "Lectures on Algebraic Statistics". I learned a lot from the book, and I enjoyed the material tremendously. (My background is in algebraic geometry, by the way.). Algebraic Statistics for Computational Biology: ISBN Author(s): Lior Pachter and Bernd Sturmfels (Editors) About the book: The quantitative analysis of biological sequence data is based on methods from statistics coupled with efficient algorithms from computer science.‘Algebraic statistics’ Application and development of techniques in Algebraic Geometry, Commutative Algebra, and Combinatorics to address problems in Statistics.

Instrumental paper: Diaconis, Persi; Sturmfels, Bernd. Algebraic algorithms for sampling from conditional distributions. Annals of Statistics 26 (), no. 1, {Algebraic statistics is the use of algebra to advance a has been useful for experimental design, parameter estimation, and hypothesis testing.

Traditionally, algebraic statistics has been associated with the design of experiments and multivariate analysis (especially time series).In recent years, the term "algebraic statistics" has been sometimes restricted, sometimes being.