Power Analysis of Finite Mixtures of Poisson Distributions

Power Analysis of Finite Mixtures of Poisson Distributions PDF Author:
Publisher:
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Category :
Languages : en
Pages :

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Power Analysis of Finite Mixtures of Poisson Distributions

Power Analysis of Finite Mixtures of Poisson Distributions PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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An Improvement of the EM Algorithm for Finite Poisson Mixtures

An Improvement of the EM Algorithm for Finite Poisson Mixtures PDF Author: Dimitris Karlis
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Finite Poisson mixtures can be used in a variety of real applications to describe count data as they can describe situations where overdispersion relative to the simple Poisson model is present. They also admit a natural interpretation: the entire population is a mixture of k subpopulations each having a Poisson distribution giving rise to the k-finite Poisson distribution. Estimating the parameters of a k-finite Poisson mixture is not easy. However, the development of the EM algorithm for finite mixtures simplified the derivation of the maximum likelihood estimates. In this paper an improvement of the standard EM algorithm for finite Poisson mixtures is introduced. It is based on the result that one from the estimating equations for the Maximum Likelihood Estimates in the case of finite Poisson mixtures is the first moment equation. Hence, replacing one of the estimating equations by this simpler form help us considerably in reducing the labour and the cost of calculating the MLE. Tables verifying the results are also given.

Mixtures of Exponential Distributions to Describe the Distribution of Poisson Means in Estimating the Number of Unobserved Classes

Mixtures of Exponential Distributions to Describe the Distribution of Poisson Means in Estimating the Number of Unobserved Classes PDF Author: Kathryn Jo-Anne Barger
Publisher:
ISBN:
Category :
Languages : en
Pages : 228

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Finite Mixture Models

Finite Mixture Models PDF Author: Geoffrey McLachlan
Publisher: John Wiley & Sons
ISBN: 047165406X
Category : Mathematics
Languages : en
Pages : 419

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Book Description
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.

A Modern Course on Statistical Distributions in Scientific Work

A Modern Course on Statistical Distributions in Scientific Work PDF Author: Ganapati P. Patil
Publisher: Springer Science & Business Media
ISBN: 9401018421
Category : Mathematics
Languages : en
Pages : 434

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Book Description
These three volumes constitute the edited Proceedings of the NATO Advanced Study Institute on Statistical Distributions in Scientific Work held at the University of Calgary from July 29 to August 10, 1974. The general title of the volumes is "Statistical Distributions in Scientific Work". The individual volumes are: Volume 1 - Models and Structures; Volume 2 - Model Building and Model Selection; and Volume 3 - Characterizations and Applications. These correspond to the three advanced seminars of the Institute devoted to the respective subject areas. The planned activities of the Institute consisted of main lectures and expositions, seminar lectures and study group dis cussions, tutorials and individual study. The activities included meetings of editorial committees to discuss editorial matters for these proceedings which consist of contributions that have gone through the usual refereeing process. A special session was organized to consider the potential of introducing a course on statistical distributions in scientific modeling in the curriculum of statistics and quantitative studies. This session is reported in Volume 2. The overall perspective for the Institute is provided by the Institute Director, Professor G. P. Pati1, in his inaugural address which appears in Volume 1. The Linnik Memorial Inaugural Lecture given by Professor C. R. Rao for the Characterizations Seminar is included in Volume 3.

Finite Mixture Distributions

Finite Mixture Distributions PDF Author: B. Everitt
Publisher: Springer Science & Business Media
ISBN: 9400958978
Category : Science
Languages : en
Pages : 148

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Book Description
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.

Statistical Analysis of Finite Mixtures of Exponential and Weibull Distributions

Statistical Analysis of Finite Mixtures of Exponential and Weibull Distributions PDF Author: Ali Riza Kaylan
Publisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 290

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Handbook of Mixture Analysis

Handbook of Mixture Analysis PDF Author: Sylvia Fruhwirth-Schnatter
Publisher: CRC Press
ISBN: 0429508247
Category : Computers
Languages : en
Pages : 522

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Book Description
Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.

Medical Applications of Finite Mixture Models

Medical Applications of Finite Mixture Models PDF Author: Peter Schlattmann
Publisher: Springer Science & Business Media
ISBN: 3540686517
Category : Medical
Languages : en
Pages : 252

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Book Description
Patients are not alike! This simple truth is often ignored in the analysis of me- cal data, since most of the time results are presented for the “average” patient. As a result, potential variability between patients is ignored when presenting, e.g., the results of a multiple linear regression model. In medicine there are more and more attempts to individualize therapy; thus, from the author’s point of view biostatis- cians should support these efforts. Therefore, one of the tasks of the statistician is to identify heterogeneity of patients and, if possible, to explain part of it with known explanatory covariates. Finite mixture models may be used to aid this purpose. This book tries to show that there are a large range of applications. They include the analysis of gene - pression data, pharmacokinetics, toxicology, and the determinants of beta-carotene plasma levels. Other examples include disease clustering, data from psychophysi- ogy, and meta-analysis of published studies. The book is intended as a resource for those interested in applying these methods.

Simulating Data with SAS

Simulating Data with SAS PDF Author: Rick Wicklin
Publisher: SAS Institute
ISBN: 1612903320
Category : Computers
Languages : en
Pages : 363

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Book Description
Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers. This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners. As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software. This book is part of the SAS Press program.