Contributions to Finite Mixture Models with Applications

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Contributions to Finite Mixture Models with Applications by : Hok Shing Kwong

Download or read book Contributions to Finite Mixture Models with Applications written by Hok Shing Kwong and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Some Theoretical Contributions to the Evaluation and Assessment of Finite Mixture Models with Applications

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ISBN 13 :
Total Pages : 176 pages
Book Rating : 4.:/5 (527 download)

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Book Synopsis Some Theoretical Contributions to the Evaluation and Assessment of Finite Mixture Models with Applications by : Volodymyr Melnykov

Download or read book Some Theoretical Contributions to the Evaluation and Assessment of Finite Mixture Models with Applications written by Volodymyr Melnykov and published by . This book was released on 2009 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Finite Mixture Models

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Publisher : John Wiley & Sons
ISBN 13 : 047165406X
Total Pages : 419 pages
Book Rating : 4.4/5 (716 download)

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Book Synopsis Finite Mixture Models by : Geoffrey McLachlan

Download or read book Finite Mixture Models written by Geoffrey McLachlan and published by John Wiley & Sons. This book was released on 2004-03-22 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mixture Models and Applications

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Publisher : Springer
ISBN 13 : 3030238768
Total Pages : 355 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Mixture Models and Applications by : Nizar Bouguila

Download or read book Mixture Models and Applications written by Nizar Bouguila and published by Springer. This book was released on 2019-08-13 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Finite Mixture Models

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Publisher :
ISBN 13 : 9789053350379
Total Pages : 206 pages
Book Rating : 4.3/5 (53 download)

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Book Synopsis Finite Mixture Models by : José Manuel Gonçalves Dias

Download or read book Finite Mixture Models written by José Manuel Gonçalves Dias and published by . This book was released on 2004 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Mixture Models

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Publisher : IMS
ISBN 13 : 9780940600324
Total Pages : 184 pages
Book Rating : 4.6/5 (3 download)

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Book Synopsis Mixture Models by : Bruce G. Lindsay

Download or read book Mixture Models written by Bruce G. Lindsay and published by IMS. This book was released on 1995 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Market Research

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Publisher : Springer
ISBN 13 : 9783319574110
Total Pages : 0 pages
Book Rating : 4.5/5 (741 download)

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Book Synopsis Handbook of Market Research by : Christian Homburg

Download or read book Handbook of Market Research written by Christian Homburg and published by Springer. This book was released on 2021-12-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this handbook, internationally renowned scholars outline the current state-of-the-art of quantitative and qualitative market research. They discuss focal approaches to market research and guide students and practitioners in their real-life applications. Aspects covered include topics on data-related issues, methods, and applications. Data-related topics comprise chapters on experimental design, survey research methods, international market research, panel data fusion, and endogeneity. Method-oriented chapters look at a wide variety of data analysis methods relevant for market research, including chapters on regression, structural equation modeling (SEM), conjoint analysis, and text analysis. Application chapters focus on specific topics relevant for market research such as customer satisfaction, customer retention modeling, return on marketing, and return on price promotions. Each chapter is written by an expert in the field. The presentation of the material seeks to improve the intuitive and technical understanding of the methods covered.

Handbook of Mixture Analysis

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Publisher : CRC Press
ISBN 13 : 0429508867
Total Pages : 388 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Handbook of Mixture Analysis by : Sylvia Fruhwirth-Schnatter

Download or read book Handbook of Mixture Analysis written by Sylvia Fruhwirth-Schnatter and published by CRC Press. This book was released on 2019-01-04 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Finite Mixture Distributions

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Publisher : Springer Science & Business Media
ISBN 13 : 9400958978
Total Pages : 148 pages
Book Rating : 4.4/5 (9 download)

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Book Synopsis Finite Mixture Distributions by : B. Everitt

Download or read book Finite Mixture Distributions written by B. Everitt and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Essays on finite mixture models

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Publisher : Rozenberg Publishers
ISBN 13 : 9036101344
Total Pages : 138 pages
Book Rating : 4.0/5 (361 download)

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Book Synopsis Essays on finite mixture models by : Abram van Dijk

Download or read book Essays on finite mixture models written by Abram van Dijk and published by Rozenberg Publishers. This book was released on 2009 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : John Wiley & Sons
ISBN 13 : 1119998441
Total Pages : 352 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Mixtures by : Kerrie L. Mengersen

Download or read book Mixtures written by Kerrie L. Mengersen and published by John Wiley & Sons. This book was released on 2011-05-03 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Hypothesis Testing in Finite Mixture Models

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ISBN 13 : 9780494433010
Total Pages : 171 pages
Book Rating : 4.4/5 (33 download)

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Book Synopsis Hypothesis Testing in Finite Mixture Models by : Pengfei Li

Download or read book Hypothesis Testing in Finite Mixture Models written by Pengfei Li and published by . This book was released on 2007 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mixture models provide a natural framework for unobserved heterogeneity in a population. They are widely applied in astronomy, biology, engineering, finance, genetics, medicine, social sciences, and other areas. An important first step for using mixture models is the test of homogeneity. Before one tries to fit a mixture model, it might be of value to know whether the data arise from a homogeneous or heterogeneous population. If the data are homogeneous, it is not even necessary to go into mixture modeling. The rejection of the homogeneous model may also have scientific implications. For example, in classical statistical genetics, it is often suspected that only a subgroup of patients have a disease gene which is linked to the marker. Detecting the existence of this subgroup amounts to the rejection of a homogeneous null model in favour of a two-component mixture model. This problem has attracted intensive research recently. This thesis makes substantial contributions in this area of research.

A Study on Variational Component Splitting Approach for Mixture Models

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis A Study on Variational Component Splitting Approach for Mixture Models by : Kamal Maanicshah Mathin Henry

Download or read book A Study on Variational Component Splitting Approach for Mixture Models written by Kamal Maanicshah Mathin Henry and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Increase in use of mobile devices and the introduction of cloud-based services have resulted in the generation of enormous amount of data every day. This calls for the need to group these data appropriately into proper categories. Various clustering techniques have been introduced over the years to learn the patterns in data that might better facilitate the classification process. Finite mixture model is one of the crucial methods used for this task. The basic idea of mixture models is to fit the data at hand to an appropriate distribution. The design of mixture models hence involves finding the appropriate parameters of the distribution and estimating the number of clusters in the data. We use a variational component splitting framework to do this which could simultaneously learn the parameters of the model and estimate the number of components in the model. The variational algorithm helps to overcome the computational complexity of purely Bayesian approaches and the over fitting problems experienced with Maximum Likelihood approaches guaranteeing convergence. The choice of distribution remains the core concern of mixture models in recent research. The efficiency of Dirichlet family of distributions for this purpose has been proved in latest studies especially for non-Gaussian data. This led us to study the impact of variational component splitting approach on mixture models based on several distributions. Hence, our contribution is the application of variational component splitting approach to design finite mixture models based on inverted Dirichlet, generalized inverted Dirichlet and inverted Beta-Liouville distributions. In addition, we also incorporate a simultaneous feature selection approach for generalized inverted Dirichlet mixture model along with component splitting as another experimental contribution. We evaluate the performance of our models with various real-life applications such as object, scene, texture, speech and video categorization.

Recent Advances in Linear Models and Related Areas

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Publisher : Springer Science & Business Media
ISBN 13 : 3790820644
Total Pages : 448 pages
Book Rating : 4.7/5 (98 download)

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Book Synopsis Recent Advances in Linear Models and Related Areas by : Shalabh

Download or read book Recent Advances in Linear Models and Related Areas written by Shalabh and published by Springer Science & Business Media. This book was released on 2008-07-11 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection contains invited papers by distinguished statisticians to honour and acknowledge the contributions of Professor Dr. Dr. Helge Toutenburg to Statistics on the occasion of his sixty-?fth birthday. These papers present the most recent developments in the area of the linear model and its related topics. Helge Toutenburg is an established statistician and currently a Professor in the Department of Statistics at the University of Munich (Germany) and Guest Professor at the University of Basel (Switzerland). He studied Mathematics in his early years at Berlin and specialized in Statistics. Later he completed his dissertation (Dr. rer. nat. ) in 1969 on optimal prediction procedures at the University of Berlin and completed the post-doctoral thesis in 1989 at the University of Dortmund on the topic of mean squared error superiority. He taught at the Universities of Berlin, Dortmund and Regensburg before joining the University of Munich in 1991. He has various areas of interest in which he has authored and co-authored over 130 research articles and 17 books. He has made pioneering contributions in several areas of statistics, including linear inference, linear models, regression analysis, quality engineering, Taguchi methods, analysis of variance, design of experiments, and statistics in medicine and dentistry.

Estimation of Finite Mixture Models

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (656 download)

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Book Synopsis Estimation of Finite Mixture Models by :

Download or read book Estimation of Finite Mixture Models written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A recorded signal frequently results from the mixture of many signals from several classifiable sources. Knowledge of the contribution of the underlying sources to the recorded signal is valuable in several applications, such as remote sensing. Such mixtures may be analyzed using finite mixture models. Historically, finite mixture models decompose a density as the sum of a finite number of component densities. Current methods for estimating the contribution of each component assume a parametric form for the mixture components. Furthermore, these methods assume a collection of samples from the mixture are observed rather than an aggregate representation of the samples, such as a histogram. This work introduces a method to address the many practical cases where parametric mixture models are insufficient to describe the mixture components. The observed mixture is assumed to occur in an aggregate representation of samples. Thus, the mixture components are represented as finite-length signals or vectors. The proposed method incorporates the first and second order statistics of the mixture components obtained from previously collected samples of the mixture components. The new method is based on the set theoretic method of successive projections onto convex sets (POCS). The set theoretic approach defines a set of feasible solutions as the intersection of sets consistent with the prior knowledge of a desirable solution. POCS is an iterative procedure used to find a point in the set of feasible solutions. This work considers several sets describing the finite mixture model, including a new model set generalizing a set based on the error-in-variables model. To illustrate the viability of the new method, comparisons are made with the expectation-maximization (EM) algorithm for mixtures with parametric components. Simulations of mixture with nonparametric components emphasize the advantages of the new method, since no other methods address mixtures with nonparametric component.

Statistical Inference Under Mixture Models

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Publisher : Springer Nature
ISBN 13 : 9819961416
Total Pages : 330 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Statistical Inference Under Mixture Models by : Jiahua Chen

Download or read book Statistical Inference Under Mixture Models written by Jiahua Chen and published by Springer Nature. This book was released on 2023-12-24 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book puts its weight on theoretical issues related to finite mixture models. It shows that a good applicant, is an applicant who understands the issues behind each statistical method. This book is intended for applicants whose interests include some understanding of the procedures they are using, while they do not have to read the technical derivations. At the same time, many researchers find most theories and techniques necessary for the development of various statistical methods, without chasing after one set of research papers, after another. Even though the book emphasizes the theory, it provides accessible numerical tools for data analysis. Readers with strength in developing statistical software, may find it useful.

Medical Applications of Finite Mixture Models

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Publisher : Springer Science & Business Media
ISBN 13 : 3540686517
Total Pages : 252 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Medical Applications of Finite Mixture Models by : Peter Schlattmann

Download or read book Medical Applications of Finite Mixture Models written by Peter Schlattmann and published by Springer Science & Business Media. This book was released on 2009-03-02 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.