Nonlinear Mixture Models

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Nonlinear Mixture Models: A Bayesian Approach

Author : Tatiana V Tatarinova
Publisher : World Scientific
ISBN 13 : 1783266279
Total Pages : 296 pages
Book Rating : 4.7/5 (832 download)

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Book Synopsis Nonlinear Mixture Models: A Bayesian Approach by : Tatiana V Tatarinova

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.

Mixed-Effects Models in S and S-PLUS

Author : José C. Pinheiro
Publisher : Springer Science & Business Media
ISBN 13 : 1441903178
Total Pages : 538 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Mixed-Effects Models in S and S-PLUS by : José C. Pinheiro

Download or read book Mixed-Effects Models in S and S-PLUS written by José C. Pinheiro and published by Springer Science & Business Media. This book was released on 2009-04-15 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: R, linear models, random, fixed, data, analysis, fit.

Nonlinear Models for Repeated Measurement Data

Author : Marie Davidian
Publisher : Routledge
ISBN 13 : 1351428152
Total Pages : 360 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Nonlinear Models for Repeated Measurement Data by : Marie Davidian

Download or read book Nonlinear Models for Repeated Measurement Data written by Marie Davidian and published by Routledge. This book was released on 2017-11-01 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.

Introduction to Population Pharmacokinetic / Pharmacodynamic Analysis with Nonlinear Mixed Effects Models

Author : Joel S. Owen
Publisher : John Wiley & Sons
ISBN 13 : 9780470582299
Total Pages : 0 pages
Book Rating : 4.5/5 (822 download)

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Book Synopsis Introduction to Population Pharmacokinetic / Pharmacodynamic Analysis with Nonlinear Mixed Effects Models by : Joel S. Owen

Download or read book Introduction to Population Pharmacokinetic / Pharmacodynamic Analysis with Nonlinear Mixed Effects Models written by Joel S. Owen and published by John Wiley & Sons. This book was released on 2014-07-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a user-friendly, hands-on introduction to the Nonlinear Mixed Effects Modeling (NONMEM) system, the most powerful tool for pharmacokinetic / pharmacodynamic analysis. • Introduces requisite background to using Nonlinear Mixed Effects Modeling (NONMEM), covering data requirements, model building and evaluation, and quality control aspects • Provides examples of nonlinear modeling concepts and estimation basics with discussion on the model building process and applications of empirical Bayesian estimates in the drug development environment • Includes detailed chapters on data set structure, developing control streams for modeling and simulation, model applications, interpretation of NONMEM output and results, and quality control • Has datasets, programming code, and practice exercises with solutions, available on a supplementary website

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Handbook of Blind Source Separation

Author : Pierre Comon
Publisher : Academic Press
ISBN 13 : 0080884946
Total Pages : 856 pages
Book Rating : 4.0/5 (88 download)

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Book Synopsis Handbook of Blind Source Separation by : Pierre Comon

Download or read book Handbook of Blind Source Separation written by Pierre Comon and published by Academic Press. This book was released on 2010-02-17 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, R&D engineers and graduates wishing to learn the core principles, methods, algorithms, and applications of Blind Source Separation. - Covers the principles and major techniques and methods in one book - Edited by the pioneers in the field with contributions from 34 of the world's experts - Describes the main existing numerical algorithms and gives practical advice on their design - Covers the latest cutting edge topics: second order methods; algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communications - Shows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications

Linear Mixed-Effects Models Using R

Author : Andrzej Gałecki
Publisher : Springer Science & Business Media
ISBN 13 : 1461439000
Total Pages : 558 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Linear Mixed-Effects Models Using R by : Andrzej Gałecki

Download or read book Linear Mixed-Effects Models Using R written by Andrzej Gałecki and published by Springer Science & Business Media. This book was released on 2013-02-05 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help readers to get familiar with the features of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software and applications. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach is used to describe the R tools for LMMs. All the classes of linear models presented in the book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariance structure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text.

International Encyclopedia of Statistical Science

Author : Miodrag Lovric
Publisher : Springer Science & Business Media
ISBN 13 : 3642048978
Total Pages : 0 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis International Encyclopedia of Statistical Science by : Miodrag Lovric

Download or read book International Encyclopedia of Statistical Science written by Miodrag Lovric and published by Springer Science & Business Media. This book was released on 2010-12-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this book is multidimensional: a) to help reviving Statistics education in many parts in the world where it is in crisis. For the first time authors from many developing countries have an opportunity to write together with the most prominent world authorities. The editor has spent several years searching for the most reputable statisticians all over the world. International contributors are either presidents of the local statistical societies, or head of the Statistics department at the main university, or the most distinguished statisticians in their countries. b) to enable any non-statistician to obtain quick and yet comprehensive and highly understandable view on certain statistical term, method or application c) to enable all the researchers, managers and practicioners to refresh their knowledge in Statistics, especially in certain controversial fields. d) to revive interest in statistics among students, since they will see its usefulness and relevance in almost all branches of Science.

Mixed Models

Author : Eugene Demidenko
Publisher : John Wiley & Sons
ISBN 13 : 1118091574
Total Pages : 768 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Mixed Models by : Eugene Demidenko

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2013-08-05 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.” —Journal of the American Statistical Association Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R. The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.

Generalized Linear Mixed Models

Author : Charles E. McCulloch
Publisher : IMS
ISBN 13 : 9780940600546
Total Pages : 100 pages
Book Rating : 4.6/5 (5 download)

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Book Synopsis Generalized Linear Mixed Models by : Charles E. McCulloch

Download or read book Generalized Linear Mixed Models written by Charles E. McCulloch and published by IMS. This book was released on 2003 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wiley Series in Probability and Statistics A modern perspective on mixed models The availability of powerful computing methods in recent decades has thrust linear and nonlinear mixed models into the mainstream of statistical application. This volume offers a modern perspective on generalized, linear, and mixed models, presenting a unified and accessible treatment of the newest statistical methods for analyzing correlated, nonnormally distributed data. As a follow-up to Searle's classic, Linear Models, and Variance Components by Searle, Casella, and McCulloch, this new work progresses from the basic one-way classification to generalized linear mixed models. A variety of statistical methods are explained and illustrated, with an emphasis on maximum likelihood and restricted maximum likelihood. An invaluable resource for applied statisticians and industrial practitioners, as well as students interested in the latest results, Generalized, Linear, and Mixed Models features: * A review of the basics of linear models and linear mixed models * Descriptions of models for nonnormal data, including generalized linear and nonlinear models * Analysis and illustration of techniques for a variety of real data sets * Information on the accommodation of longitudinal data using these models * Coverage of the prediction of realized values of random effects * A discussion of the impact of computing issues on mixed models

Mixed Effects Models for the Population Approach

Author : Marc Lavielle
Publisher : CRC Press
ISBN 13 : 1482226510
Total Pages : 380 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Mixed Effects Models for the Population Approach by : Marc Lavielle

Download or read book Mixed Effects Models for the Population Approach written by Marc Lavielle and published by CRC Press. This book was released on 2014-07-14 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wide-Ranging Coverage of Parametric Modeling in Linear and Nonlinear Mixed Effects ModelsMixed Effects Models for the Population Approach: Models, Tasks, Methods and Tools presents a rigorous framework for describing, implementing, and using mixed effects models. With these models, readers can perform parameter estimation and modeling across a whol

Nonlinear Regression with R

Author : Christian Ritz
Publisher : Springer Science & Business Media
ISBN 13 : 0387096167
Total Pages : 151 pages
Book Rating : 4.3/5 (87 download)

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Book Synopsis Nonlinear Regression with R by : Christian Ritz

Download or read book Nonlinear Regression with R written by Christian Ritz and published by Springer Science & Business Media. This book was released on 2008-12-11 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: - Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.

Linear Mixed Models

Author : Brady T. West
Publisher : CRC Press
ISBN 13 : 1420010433
Total Pages : 376 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Linear Mixed Models by : Brady T. West

Download or read book Linear Mixed Models written by Brady T. West and published by CRC Press. This book was released on 2006-11-22 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-nav

Linear and Nonlinear Models for the Analysis of Repeated Measurements

Author : Edward Vonesh
Publisher : CRC Press
ISBN 13 : 9780824782481
Total Pages : 590 pages
Book Rating : 4.7/5 (824 download)

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Book Synopsis Linear and Nonlinear Models for the Analysis of Repeated Measurements by : Edward Vonesh

Download or read book Linear and Nonlinear Models for the Analysis of Repeated Measurements written by Edward Vonesh and published by CRC Press. This book was released on 1996-11-01 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrates the latest theory, methodology and applications related to the design and analysis of repeated measurement. The text covers a broad range of topics, including the analysis of repeated measures design, general crossover designs, and linear and nonlinear regression models. It also contains a 3.5 IBM compatible disk, with software to implement immediately the techniques.

Nonlinear Blind Source Separation and Blind Mixture Identification

Author : Yannick Deville
Publisher : Springer Nature
ISBN 13 : 3030649776
Total Pages : 75 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Nonlinear Blind Source Separation and Blind Mixture Identification by : Yannick Deville

Download or read book Nonlinear Blind Source Separation and Blind Mixture Identification written by Yannick Deville and published by Springer Nature. This book was released on 2021-02-02 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures. Another attractive feature of the book is that it is based on a coherent framework. More precisely, the authors first present a general procedure for developing blind source separation methods. Then, all reported methods are defined with respect to this procedure. This allows the reader not only to more easily follow the description of each method but also to see how these methods relate to one another. The coherence of this book also results from the fact that the same notations are used throughout the chapters for the quantities (source signals and so on) that are used in various methods. Finally, among the quite varied types of processing methods that are presented in this book, a significant part of this description is dedicated to methods based on artificial neural networks, especially recurrent ones, which are currently of high interest to the data analysis and machine learning community in general, beyond the more specific signal processing and blind source separation communities.

Mixed Models

Author : Eugene Demidenko
Publisher : John Wiley & Sons
ISBN 13 : 0471726133
Total Pages : 732 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Mixed Models by : Eugene Demidenko

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2005-01-28 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: A rigorous, self-contained examination of mixed model theory and application Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. Paying special attention to algorithms and their implementations, the book discusses: Modeling of complex clustered or longitudinal data Modeling data with multiple sources of variation Modeling biological variety and heterogeneity Mixed model as a compromise between the frequentist and Bayesian approaches Mixed model for the penalized log-likelihood Healthy Akaike Information Criterion (HAIC) How to cope with parameter multidimensionality How to solve ill-posed problems including image reconstruction problems Modeling of ensemble shapes and images Statistics of image processing Major results and points of discussion at the end of each chapter along with "Summary Points" sections make this reference not only comprehensive but also highly accessible for professionals and students alike in a broad range of fields such as cancer research, computer science, engineering, and industry.

Applied Statistics in Agricultural, Biological, and Environmental Sciences

Author : Barry Glaz
Publisher : John Wiley & Sons
ISBN 13 : 0891183590
Total Pages : 672 pages
Book Rating : 4.8/5 (911 download)

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Book Synopsis Applied Statistics in Agricultural, Biological, and Environmental Sciences by : Barry Glaz

Download or read book Applied Statistics in Agricultural, Biological, and Environmental Sciences written by Barry Glaz and published by John Wiley & Sons. This book was released on 2020-01-22 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Better experimental design and statistical analysis make for more robust science. A thorough understanding of modern statistical methods can mean the difference between discovering and missing crucial results and conclusions in your research, and can shape the course of your entire research career. With Applied Statistics, Barry Glaz and Kathleen M. Yeater have worked with a team of expert authors to create a comprehensive text for graduate students and practicing scientists in the agricultural, biological, and environmental sciences. The contributors cover fundamental concepts and methodologies of experimental design and analysis, and also delve into advanced statistical topics, all explored by analyzing real agronomic data with practical and creative approaches using available software tools. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.