Latent Markov Models for Longitudinal Data, Bartolucci, Francesco

Автор: Bartolucci, Francesco
Название: Latent Markov Models for Longitudinal Data
ISBN: 1032477547 ISBN-13(EAN): 9781032477541
Издательство: Taylor&Francis
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Цена: 46950.00 T
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Автор: Kees van Montfort; Johan H.L. Oud; Albert Satorra
Название: Longitudinal Research with Latent Variables
ISBN: 3642117597 ISBN-13(EAN): 9783642117596
Издательство: Springer
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Цена: 111790.00 T
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Описание: Since Charles Spearman published his seminal paper on factor analysis in 1904 and Karl Joresk og replaced the observed variables in an econometric structural equation model by latent factors in 1970, causal modelling by means of latent variables has become the standard in the social and behavioural sciences.

Автор: Yuriy E Obzherin
Название: Semi-Markov Models
ISBN: 0128022124 ISBN-13(EAN): 9780128022122
Издательство: Elsevier Science
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Цена: 77470.00 T
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Описание: Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes valuable methodology which can be used by readers to build mathematical models of a wide class of systems for various applications. In particular, this information can be applied to build models of reliability, queuing systems, and technical control. . Beginning with a brief introduction to the area, the book covers semi-Markov models for different control strategies in one-component systems, defining their stationary characteristics of reliability and efficiency, and utilizing the method of asymptotic phase enlargement developed by V.S. Korolyuk and A.F. Turbin. The work then explores semi-Markov models of latent failures control in two-component systems. Building on these results, solutions are provided for the problems of optimal periodicity of control execution. Finally, the book presents a comparative analysis of analytical and imitational modeling of some one- and two-component systems, before discussing practical applications of the results

Автор: Kees van Montfort; Johan H.L. Oud; Albert Satorra
Название: Longitudinal Research with Latent Variables
ISBN: 3642425720 ISBN-13(EAN): 9783642425721
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Since Charles Spearman published his seminal paper on factor analysis in 1904 and Karl Joresk og replaced the observed variables in an econometric structural equation model by latent factors in 1970, causal modelling by means of latent variables has become the standard in the social and behavioural sciences.

Автор: Maurizio Carpita; Eugenio Brentari; El Mostafa Qan
Название: Advances in Latent Variables
ISBN: 3319380230 ISBN-13(EAN): 9783319380230
Издательство: Springer
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Цена: 79190.00 T
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Описание: The book, belonging to the series "Studies in Theoretical and Applied Statistics- Selected Papers from the Statistical Societies", presents a peer-reviewed selection of contributions on relevant topics organized by the editors on the occasion of the SIS 2013 Statistical Conference "Advances in Latent Variables.

Автор: Maurizio Carpita; Eugenio Brentari; El Mostafa Qan
Название: Advances in Latent Variables
ISBN: 3319029665 ISBN-13(EAN): 9783319029665
Издательство: Springer
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Цена: 79190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book, belonging to the series "Studies in Theoretical and Applied Statistics- Selected Papers from the Statistical Societies", presents a peer-reviewed selection of contributions on relevant topics organized by the editors on the occasion of the SIS 2013 Statistical Conference "Advances in Latent Variables.

Автор: R. Langeheine; J. Rost
Название: Latent Trait and Latent Class Models
ISBN: 1475756461 ISBN-13(EAN): 9781475756463
Издательство: Springer
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Цена: 46570.00 T
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Описание: This volume is based on an international conference held at the Institute for Science Education (IPN) in Kiel in August 1985.

Автор: Michael C. Edwards, Robert C. MacCallum
Название: Current Topics in the Theory and Application of Latent Variable Models
ISBN: 1848729510 ISBN-13(EAN): 9781848729513
Издательство: Taylor&Francis
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Цена: 148010.00 T
Наличие на складе: Невозможна поставка.
Описание: This book presents recent developments in the theory and application of latent variable models (LVMs) by some of the most prominent researchers in the field. Topics covered involve a range of LVM frameworks including item response theory, structural equation modeling, factor analysis, and latent curve modeling, as well as various non-standard data structures and innovative applications. The book is divided into two sections, although several chapters cross these content boundaries.  Part one focuses on complexities which involve the adaptation of latent variables models in research problems where real-world conditions do not match conventional assumptions.  Chapters in this section cover issues such as analysis of dyadic data and complex survey data, as well as analysis of categorical variables.  Part two of the book focuses on drawing real-world meaning from results obtained in LVMs. In this section there are chapters examining issues involving assessment of model fit, the nature of uncertainty in parameter estimates, inferences, and the nature of latent variables and individual differences. This book appeals to researchers and graduate students interested in the theory and application of latent variable models. As such, it serves as a supplementary reading in graduate level courses on latent variable models. Prerequisites include basic knowledge of latent variable models.

Автор: Zwiernik, Piotr
Название: Semialgebraic Statistics and Latent Tree Models
ISBN: 0367377497 ISBN-13(EAN): 9780367377496
Издательство: Taylor&Francis
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Цена: 65320.00 T
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Semialgebraic Statistics and Latent Tree Models explains how to analyze statistical models with hidden (latent) variables. It takes a systematic, geometric approach to studying the semialgebraic structure of latent tree models.

The first part of the book gives a general introduction to key concepts in algebraic statistics, focusing on methods that are helpful in the study of models with hidden variables. The author uses tensor geometry as a natural language to deal with multivariate probability distributions, develops new combinatorial tools to study models with hidden data, and describes the semialgebraic structure of statistical models.

The second part illustrates important examples of tree models with hidden variables. The book discusses the underlying models and related combinatorial concepts of phylogenetic trees as well as the local and global geometry of latent tree models. It also extends previous results to Gaussian latent tree models.

This book shows you how both combinatorics and algebraic geometry enable a better understanding of latent tree models. It contains many results on the geometry of the models, including a detailed analysis of identifiability and the defining polynomial constraints.

Автор: Marcoulides, George A.
Название: Latent Variable and Latent Structure Models
ISBN: 0415649617 ISBN-13(EAN): 9780415649612
Издательство: Taylor&Francis
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Цена: 57150.00 T
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Название: Current topics in the theory and application of latent variable models
ISBN: 0415637783 ISBN-13(EAN): 9780415637787
Издательство: Taylor&Francis
Рейтинг:
Цена: 53070.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents recent developments in the theory and application of latent variable models (LVMs) by some of the most prominent researchers in the field. Topics covered involve a range of LVM frameworks including item response theory, structural equation modeling, factor analysis, and latent curve modeling, as well as various non-standard data structures and innovative applications. The book is divided into two sections, although several chapters cross these content boundaries.  Part one focuses on complexities which involve the adaptation of latent variables models in research problems where real-world conditions do not match conventional assumptions.  Chapters in this section cover issues such as analysis of dyadic data and complex survey data, as well as analysis of categorical variables.  Part two of the book focuses on drawing real-world meaning from results obtained in LVMs. In this section there are chapters examining issues involving assessment of model fit, the nature of uncertainty in parameter estimates, inferences, and the nature of latent variables and individual differences. This book appeals to researchers and graduate students interested in the theory and application of latent variable models. As such, it serves as a supplementary reading in graduate level courses on latent variable models. Prerequisites include basic knowledge of latent variable models.

Автор: Gregory R. Hancock, Jeffrey R. Harring, George B. Macready
Название: Advances in Latent Class Analysis: A Festschrift in Honor of C. Mitchell Dayton
ISBN: 164113562X ISBN-13(EAN): 9781641135627
Издательство: Mare Nostrum (Eurospan)
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Цена: 95170.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time of inception, latent class analysis was viewed primarily as a categorical data analysis technique, often framed as a factor analysis model where both the measured variable indicators and underlying latent variables are categorical. Today, however, it rests within much broader mixture and diagnostic modeling framework, integrating measured and latent variables that may be categorical and/or continuous, and where latent classes serve to define the subpopulations for whom many aspects of the focal measured and latent variable model may differ. For latent class analysis to take these developmental leaps required contributions that were methodological, certainly, as well as didactic. Among the leaders on both fronts was C. Mitchell “Chan” Dayton, at the University of Maryland, whose work in latent class analysis spanning several decades helped the method to expand and reach its current potential. The current volume in the Center for Integrated Latent Variable Research (CILVR) series reflects the diversity that is latent class analysis today, celebrating work related to, made possible by, and inspired by Chan’s noted contributions, and signaling the even more exciting future yet to come.