Finite Mixture Distributions


Finite Mixture Distributions
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Statistical Analysis Of Finite Mixture Distributions


Statistical Analysis Of Finite Mixture Distributions
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Author : D. M. Titterington
language : en
Publisher:
Release Date : 1985

Statistical Analysis Of Finite Mixture Distributions written by D. M. Titterington and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.


In this book, the authors give a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions.



Finite Mixture Distributions


Finite Mixture Distributions
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Author : B. Everitt
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-08

Finite Mixture Distributions written by B. Everitt 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 2013-03-08 with Science categories.


Finite mixture distributions arise in a variety of applications ranging from the length distribution of fish to the content of DNA in the nuclei of liver cells. The literature surrounding them is large and goes back to the end of the last century when Karl Pearson published his well-known paper on estimating the five parameters in a mixture of two normal distributions. In this text we attempt to review this literature and in addition indicate the practical details of fitting such distributions to sample data. Our hope is that the monograph will be useful to statisticians interested in mixture distributions and to re search workers in other areas applying such distributions to their data. We would like to express our gratitude to Mrs Bertha Lakey for typing the manuscript. Institute oj Psychiatry B. S. Everitt University of London D. l Hand 1980 CHAPTER I General introduction 1. 1 Introduction This monograph is concerned with statistical distributions which can be expressed as superpositions of (usually simpler) component distributions. Such superpositions are termed mixture distributions or compound distributions. For example, the distribution of height in a population of children might be expressed as follows: h(height) = fg(height: age)f(age)d age (1. 1) where g(height: age) is the conditional distribution of height on age, and/(age) is the age distribution of the children in the population.



Finite Mixture Models


Finite Mixture Models
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Author : Geoffrey McLachlan
language : en
Publisher: John Wiley & Sons
Release Date : 2004-03-22

Finite Mixture Models written by Geoffrey McLachlan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-22 with Mathematics categories.


An up-to-date, comprehensive account of major issues in finitemixture modeling This volume provides an up-to-date account of the theory andapplications of modeling via finite mixture distributions. With anemphasis on the applications of mixture models in both mainstreamanalysis and other areas such as unsupervised pattern recognition,speech recognition, and medical imaging, the book describes theformulations of the finite mixture approach, details itsmethodology, discusses aspects of its implementation, andillustrates its application in many common statisticalcontexts. Major issues discussed in this book include identifiabilityproblems, actual fitting of finite mixtures through use of the EMalgorithm, properties of the maximum likelihood estimators soobtained, assessment of the number of components to be used in themixture, and the applicability of asymptotic theory in providing abasis for the solutions to some of these problems. The author alsoconsiders how the EM algorithm can be scaled to handle the fittingof mixture models to very large databases, as in data miningapplications. This comprehensive, practical guide: * Provides more than 800 references-40% published since 1995 * Includes an appendix listing available mixture software * Links statistical literature with machine learning and patternrecognition literature * Contains more than 100 helpful graphs, charts, and tables Finite Mixture Models is an important resource for both applied andtheoretical statisticians as well as for researchers in the manyareas in which finite mixture models can be used to analyze data.



Finite Mixture Of Skewed Distributions


Finite Mixture Of Skewed Distributions
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Author : Víctor Hugo Lachos Dávila
language : en
Publisher: Springer
Release Date : 2018-11-12

Finite Mixture Of Skewed Distributions written by Víctor Hugo Lachos Dávila and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-12 with Mathematics categories.


This book presents recent results in finite mixtures of skewed distributions to prepare readers to undertake mixture models using scale mixtures of skew normal distributions (SMSN). For this purpose, the authors consider maximum likelihood estimation for univariate and multivariate finite mixtures where components are members of the flexible class of SMSN distributions. This subclass includes the entire family of normal independent distributions, also known as scale mixtures of normal distributions (SMN), as well as the skew-normal and skewed versions of some other classical symmetric distributions: the skew-t (ST), the skew-slash (SSL) and the skew-contaminated normal (SCN), for example. These distributions have heavier tails than the typical normal one, and thus they seem to be a reasonable choice for robust inference. The proposed EM-type algorithm and methods are implemented in the R package mixsmsn, highlighting the applicability of the techniques presented in the book. This work is a useful reference guide for researchers analyzing heterogeneous data, as well as a textbook for a graduate-level course in mixture models. The tools presented in the book make complex techniques accessible to applied researchers without the advanced mathematical background and will have broad applications in fields like medicine, biology, engineering, economic, geology and chemistry.



Essays On Finite Mixture Models


Essays On Finite Mixture Models
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Author : Abram van Dijk
language : en
Publisher: Rozenberg Publishers
Release Date : 2009

Essays On Finite Mixture Models written by Abram van Dijk and has been published by Rozenberg Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.


Finite mixture distributions are a weighted average of a finite number of distributions. The latter are usually called the mixture components. The weights are usually described by a multinomial distribution and are sometimes called mixing proportions. The mixture components may be the same type of distributions with di®erent parameter values but they may also be completely different distributions. Therefore, finite mixture distributions are very °exible for modeling data. They are frequently used as a building block within many modern econometric models. The specification of the mixture distribution depends on the modeling problem at hand. In this thesis, we introduce new applications of finite mixtures to deal with several di®erent modeling issues. Each chapter of the thesis focusses on a specific modeling issue. The parameters of some of the resulting models can be estimated using standard techniques but for some of the chapters we need to develop new estimation and inference methods. To illustrate how the methods can be applied, we analyze at least one empirical data set for each approach. These data sets cover a wide range of research fields, such as macroeconomics, marketing, and political science. We show the usefulness of the methods and, in some cases, the improvement over previous methods in the literature.



Mixtures


Mixtures
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Author : Kerrie L. Mengersen
language : en
Publisher: John Wiley & Sons
Release Date : 2011-05-03

Mixtures written by Kerrie L. Mengersen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-03 with Mathematics categories.


This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject. The applications are drawn from scientific discipline, including biostatistics, computer science, ecology and finance. This area of statistics is important to a range of disciplines, and its methodology attracts interest from researchers in the fields in which it can be applied.



Finite Mixture And Markov Switching Models


Finite Mixture And Markov Switching Models
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Author : Sylvia Frühwirth-Schnatter
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-11-24

Finite Mixture And Markov Switching Models written by Sylvia Frühwirth-Schnatter 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 2006-11-24 with Mathematics categories.


The past decade has seen powerful new computational tools for modeling which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book is the first to offer a systematic presentation of the Bayesian perspective of finite mixture modelling. The book is designed to show finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated. Presenting its concepts informally without sacrificing mathematical correctness, it will serve a wide readership including statisticians as well as biologists, economists, engineers, financial and market researchers.



Mixture Models And Applications


Mixture Models And Applications
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Author : Nizar Bouguila
language : en
Publisher: Springer
Release Date : 2019-08-13

Mixture Models And Applications written by Nizar Bouguila and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-13 with Technology & Engineering categories.


This book focuses on recent advances, approaches, theories and applications related to mixture models. In particular, it presents recent unsupervised and semi-supervised frameworks that consider mixture models as their main tool. The chapters considers mixture models involving several interesting and challenging problems such as parameters estimation, model selection, feature selection, etc. The goal of this book is to summarize the recent advances and modern approaches related to these problems. Each contributor presents novel research, a practical study, or novel applications based on mixture models, or a survey of the literature. Reports advances on classic problems in mixture modeling such as parameter estimation, model selection, and feature selection; Present theoretical and practical developments in mixture-based modeling and their importance in different applications; Discusses perspectives and challenging future works related to mixture modeling.



Mixtures


Mixtures
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Author : Kerrie L. Mengersen
language : en
Publisher: Wiley
Release Date : 2011-06-13

Mixtures written by Kerrie L. Mengersen and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-13 with Mathematics categories.


This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject. The applications are drawn from scientific discipline, including biostatistics, computer science, ecology and finance. This area of statistics is important to a range of disciplines, and its methodology attracts interest from researchers in the fields in which it can be applied.



Clustering With Finite Data From Semi Parametric Mixture Distributions


Clustering With Finite Data From Semi Parametric Mixture Distributions
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Author : Yong Wang
language : en
Publisher:
Release Date : 1999

Clustering With Finite Data From Semi Parametric Mixture Distributions written by Yong Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Cluster analysis categories.