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: B.K. Sinha; N.K. Mandal; Manisha Pal; P. Das Название: Optimal Mixture Experiments ISBN: 8132217853 ISBN-13(EAN): 9788132217855 Издательство: Springer Рейтинг: Цена: 88500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Opening with the basics of regression designs, this book reviews linear and quadratic Scheffe mixture models, applies the Darroch-Waller three-component quadratic mixture model to the general q-component model, discusses non-standard mixture designs and more.
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: Piepel Gregory Название: Models and Designs for Generalizations of Mixture Experiments Where the Response Depends on the Total Amount ISBN: 0530007584 ISBN-13(EAN): 9780530007588 Издательство: Неизвестно Рейтинг: Цена: 80930.00 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.
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: 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.
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: Bouguila Nizar, Fan Wentao Название: Mixture Models and Applications ISBN: 3030238784 ISBN-13(EAN): 9783030238780 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
A Gaussian Mixture Model Approach To Classifying Response Types.- Interactive Generation Of Calligraphic Trajectories From Gaussian Mixtures.- Mixture models for the analysis, edition, and synthesis of continuous time series.- Multivariate Bounded Asymmetric Gaussian Mixture Model.- Online Recognition Via A Finite Mixture Of Multivariate Generalized Gaussian Distributions.- L2 Normalized Data Clustering Through the Dirichlet Process Mixture Model of Von Mises Distributions with Localized Feature Selection.- Deriving Probabilistic SVM Kernels From Exponential Family Approximations to Multivariate Distributions for Count Data.- Toward an Efficient Computation of Log-likelihood Functions in Statistical Inference: Overdispersed Count Data Clustering.- A Frequentist Inference Method Based On Finite Bivariate And Multivariate Beta Mixture Models.- Finite Inverted Beta-Liouville Mixture Models with Variational Component Splitting.- Online Variational Learning for Medical Image Data Clustering.- Color Image Segmentation using Semi-Bounded Finite Mixture Models by Incorporating Mean Templates.- Medical Image Segmentation Based on Spatially Constrained Inverted Beta-Liouville Mixture Models.- Flexible Statistical Learning Model For Unsupervised Image Modeling And Segmentation.
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: Shelton John Название: Testing Lack of Fit in a Mixture Model ISBN: 0530006693 ISBN-13(EAN): 9780530006697 Издательство: Неизвестно Рейтинг: Цена: 114030.00 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: 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: Ivan Nagy; Evgenia Suzdaleva Название: Algorithms and Programs of Dynamic Mixture Estimation ISBN: 3319646702 ISBN-13(EAN): 9783319646701 Издательство: Springer Рейтинг: Цена: 51230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models.
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