Download or read book Mixture Modelling for Medical and Health Sciences written by Shu-Kay Ng and published by Chapman & Hall/CRC. This book was released on 2019 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mixture Modelling for Medical and Health Sciencesprovides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through comprehensive analyses of real and practical examples taken from real-life research problems in medical and health sciences. This approach represents balance between "theory" and "practice", stimulating readers and enhancing their capacity to apply mixture models in data analysis. Full of reproducible examples using software code and publicly-available data, the book is suitable for graduate-level students, researchers, and practitioners who have a basic grounding in statistics and would like to explore the use of mixture models to analyse their experiments and research data. Features An in-depth account of the most up-to-date mixture modelling techniques from auser perspective. Extensive real-life examples - from typical daily problems to complex data modelling. Emphasis on the use of a wide variety of component densities for statistical modelling. Coverage of the latest random-effects models in modelling complex correlated data. An accompanying website to provide supplementary materials, including software and detailed programming code, and links to available data sources. Provision of R and Fortran code for readers who want to do analysis of their own data using mixture models. Shu-Kay Angus Ngis Professor of Biostatistics in the School of Medicine at the Griffith University, Australia. Dr Ng has published extensively on his research interests, which include cluster analysis, pattern recognition, random-effects modelling, and survival analysis. Liming Xiangis Associate Professor of Statistics in the School of Physical & Mathematical Sciences at the Nanyang Technological University, Singapore. Her research interests include survival analysis, longitudinal/clustered data analysis and mixture models. Kelvin Kai-wing Yauis Professor of Statistics in the Department of Management Sciences at the City University of Hong Kong. He has been involved in various interdisciplinary research projects, with journal publications in statistics, medical and health science journals on topics such as mixed effects models, survival analysis and statistical modelling in general. lling techniques from auser perspective. Extensive real-life examples - from typical daily problems to complex data modelling. Emphasis on the use of a wide variety of component densities for statistical modelling. Coverage of the latest random-effects models in modelling complex correlated data. An accompanying website to provide supplementary materials, including software and detailed programming code, and links to available data sources. Provision of R and Fortran code for readers who want to do analysis of their own data using mixture models. Shu-Kay Angus Ngis Professor of Biostatistics in the School of Medicine at the Griffith University, Australia. Dr Ng has published extensively on his research interests, which include cluster analysis, pattern recognition, random-effects modelling, and survival analysis. Liming Xiangis Associate Professor of Statistics in the School of Physical & Mathematical Sciences at the Nanyang Technological University, Singapore. Her research interests include survival analysis, longitudinal/clustered data analysis and mixture models. Kelvin Kai-wing Yauis Professor of Statistics in the Department of Management Sciences at the City University of Hong Kong. He has been involved in various interdisciplinary research projects, with journal publications in statistics, medical and health science journals on topics such as mixed effects models, survival analysis and statistical modelling in general. the Griffith University, Australia. Dr Ng has published extensively on his research interests, which include cluster analysis, pattern recognition, random-effects modelling, and survival analysis. Liming Xiangis Associate Professor of Statistics in the School of Physical & Mathematical Sciences at the Nanyang Technological University, Singapore. Her research interests include survival analysis, longitudinal/clustered data analysis and mixture models. Kelvin Kai-wing Yauis Professor of Statistics in the Department of Management Sciences at the City University of Hong Kong. He has been involved in various interdisciplinary research projects, with journal publications in statistics, medical and health science journals on topics such as mixed effects models, survival analysis and statistical modelling in general.
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.
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.
Download or read book Applications of Finite Mixture Models in Medicine written by Shu Kay Angus Ng and published by . This book was released on 1999 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book Finite Mixture and Markov Switching Models written by Sylvia Frühwirth-Schnatter and published by Springer Science & Business Media. This book was released on 2006-11-24 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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:
Download or read book Nonlinear Mixture Models A Bayesian Approach written by Tatiana V Tatarinova and published by World Scientific. This book was released on 2014-12-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, written by two mathematicians from the University of Southern California, provides a broad introduction to the important subject of nonlinear mixture models from a Bayesian perspective. It contains background material, a brief description of Markov chain theory, as well as novel algorithms and their applications. It is self-contained and unified in presentation, which makes it ideal for use as an advanced textbook by graduate students and as a reference for independent researchers. The explanations in the book are detailed enough to capture the interest of the curious reader, and complete enough to provide the necessary background material needed to go further into the subject and explore the research literature.In this book the authors present Bayesian methods of analysis for nonlinear, hierarchical mixture models, with a finite, but possibly unknown, number of components. These methods are then applied to various problems including population pharmacokinetics and gene expression analysis. In population pharmacokinetics, the nonlinear mixture model, based on previous clinical data, becomes the prior distribution for individual therapy. For gene expression data, one application included in the book is to determine which genes should be associated with the same component of the mixture (also known as a clustering problem). The book also contains examples of computer programs written in BUGS. This is the first book of its kind to cover many of the topics in this field.
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:
Download or read book Finite Mixture of Skewed Distributions written by Víctor Hugo Lachos Dávila and published by Springer. This book was released on 2018-11-12 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Global Optimization of Finite Mixture Models written by Jeffrey W. Heath and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book Computational Methods in Finite Mixtures Using Approximate Information and Regression Linked to the Mixture Mean written by Andrew Martin Raim and published by . This book was released on 2014 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finite mixture distributions are used in applications because of their ability to support heterogeneity. They also present interesting analytical challenges, often requiring special consideration in the selection of an appropriate model, inference of unknown parameters, and identifiability. The main contributions of this thesis are providing an approximation to the information matrix of a finite mixture of an arbitrary member of the exponential family, and a novel extension of the generalized linear model (GLM) with an underlying finite mixture distribution.
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:
Download or read book Development of Finite Mixture Models to Assess the Adequacy of Non identical Multiple Tooled Manufacturing Processes written by Allen Thomas Bracken and published by . This book was released on 2005 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Finite Mixture Model Specifications Accommodating Treatment Nonresponse in Experimental Research written by John Andrew Wasko and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Group Sequential Testing of Homogeneity in Finite Mixture Models written by Yin Cui and published by . This book was released on 2007 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
