Автор: Olga Moreira Название: Handbook of Mixture Analysis ISBN: 1774077086 ISBN-13(EAN): 9781774077085 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 160770.00 T Наличие на складе: Нет в наличии. Описание: Presents a collection of peer-reviewed articles featuring several statistical data analysis methods based on mixture models and their applications in scientific domains such as data mining, machine learning, physics, mechanical engineering, signal processing, economics, cosmology, and computational medicine.
Автор: Tatarinova Tatiana, Schumitzky Alan Название: Nonlinear Mixture Models: A Bayesian Approach ISBN: 1848167563 ISBN-13(EAN): 9781848167568 Издательство: World Scientific Publishing Рейтинг: Цена: 95040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides an introduction to the important subject of nonlinear mixture models from a Bayesian perspective. This title contains background material, a brief description of Markov chain theory, as well as novel algorithms and their applications.
Автор: Visser Название: Mixture and Hidden Markov Models with R ISBN: 3031014383 ISBN-13(EAN): 9783031014383 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book discusses mixture and hidden Markov models for modeling behavioral data. Hidden Markov models can be viewed as an extension of mixture models, to model transitions between states over time.
Автор: Wickrama, Kandauda A.s. Lee, Tae Kyoung (university Of Georgia, Usa) O`neal, Catherine Walker (university Of Georgia, Usa) Lorenz, Frederick O. Название: Higher-order growth curves and mixture modeling with mplus ISBN: 0367711265 ISBN-13(EAN): 9780367711269 Издательство: Taylor&Francis Рейтинг: Цена: 59190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps.The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two using normal and non-normal (e.g., categorical) data. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web.New to this edition:* Two new chapters providing a stepwise introduction and practical guide to the application of second-order growth curves and mixture models with categorical outcomes using the Mplus program. Complete with exercises, answer keys, and downloadable data files.* Updated illustrative examples using Mplus 8.0 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data.This text is ideal for use in graduate courses or workshops on advanced structural equation, multilevel, longitudinal or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) across the social and behavioral sciences.
Автор: Wickrama Kandauda A. S., Lee Tae Kyoung, O`Neal Catherine Walker Название: Higher-Order Growth Curves and Mixture Modeling with Mplus: A Practical Guide ISBN: 0367746204 ISBN-13(EAN): 9780367746209 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps.
Автор: Ng, Shu-Kay Название: Mixture Modelling for Medical and Health Sciences ISBN: 0367729334 ISBN-13(EAN): 9780367729332 Издательство: Taylor&Francis Рейтинг: Цена: 50010.00 T Наличие на складе: Нет в наличии.
Автор: Bouguila Nizar, Fan Wentao Название: Mixture Models and Applications ISBN: 303023875X ISBN-13(EAN): 9783030238759 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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.
Автор: Lachos D?vila Название: Finite Mixture of Skewed Distributions ISBN: 3319980289 ISBN-13(EAN): 9783319980287 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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).
Автор: Shelton John Название: Testing Lack of Fit in a Mixture Model ISBN: 0530006685 ISBN-13(EAN): 9780530006680 Издательство: Неизвестно Рейтинг: Цена: 80930.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Abstract: A common problem in modeling the response surface in most systems, and in particular in a mixture system, is that of detecting lack of fit, or inadequancy, of a fitted model of the form E(Y) = Xg, in comparison to a model of the form E{Y) = Xe, + X B postulated as the true model. One method for detecting lack of fit involves comparing the value of the response observed at certain locations in the factor space, called "check points," with the value of the response that the fitted model predicts at these same check points. The observations at the check points are used only for testing lack of fit and are not used in fitting the model. It is shown that under the usual assumptions of independent and normally distributed errors, the lack of fit test statistic which uses the data at the check points is an F statistic. When no lack of fit is present the statistic possesses a central F distribution, but in general, in the presence of lack of fit, the statistic possesses a doubly noncentral F distribution. The power of this F test depends on the location of the check points in the factor space through its noncentrality parameters. A method of selecting check points that maximize the power of the test for lack of fit through their influence on the numerator noncentrality parameter is developed. A second method for detecting lack of fit relies on replicated response observations. The residual sum of squares from the fitted model is partitioned into a pure error variation component and into a lack of fit variation component. Lack of fit is detected if the lack of fit variation is large in comparison to the pure error variation. This method can be generalized when "near neighbor" observations must be substituted for replicates. In this case, the test statistic (assuming independent and normally distributed errors) has a central F distribution when the fitted model is adequate and a doubly noncentral F distribution under lack of fit. The arrangement of near neighbors is seen to affect the testing procedure and its power. Dissertation Discovery Company and University of Florida are dedicated to making scholarly works more discoverable and accessible throughout the world. This dissertation, "Testing Lack of Fit in a Mixture Model" by John Thomas Shelton, was obtained from University of Florida and is being sold with permission from the author. A digital copy of this work may also be found in the university's institutional repository, IR@UF. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation.
Автор: Sylvia Fr?hwirth-Schnatter Название: Finite Mixture and Markov Switching Models ISBN: 144192194X ISBN-13(EAN): 9781441921949 Издательство: Springer Рейтинг: Цена: 144410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is the first to offer a systematic presentation of the Bayesian perspective of finite mixture modeling, showing how finite mixture and Markov switching models are formulated, what structures they imply on the data, their potential uses, and how they are estimated.
Автор: Peter Schlattmann Название: Medical Applications of Finite Mixture Models ISBN: 3642088163 ISBN-13(EAN): 9783642088162 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows how to model heterogeneity in medical research with covariate adjusted finite mixture models. The areas of application include epidemiology, gene expression data, disease mapping, meta-analysis, neurophysiology and pharmacology.
Автор: Piepel Gregory Название: Models and Designs for Generalizations of Mixture Experiments Where the Response Depends on the Total Amount ISBN: 0530007592 ISBN-13(EAN): 9780530007595 Издательство: Неизвестно Рейтинг: Цена: 114030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Abstract: Development of statistical experimental designs and models for experiments with mixtures (formulations) when response variables depend on (i) the relative proportions of the mixture components and the total amount of the mixture, (ii) the amounts of mixture components, or (iii) component-wise proportions. Dissertation Discovery Company and University of Florida are dedicated to making scholarly works more discoverable and accessible throughout the world. This dissertation, "Models and Designs for Generalizations of Mixture Experiments Where the Response Depends on the Total Amount" by Gregory Frank Piepel, was obtained from University of Florida and is being sold with permission from the author. A digital copy of this work may also be found in the university's institutional repository, IR@UF. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation.
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