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Semialgebraic Statistics and Latent Tree Models

Semialgebraic Statistics and Latent Tree Models explains how to analyze statistical models with hidden (latent) variables. It takes a;

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Semialgebraic Statistics and Latent Tree Models

Semialgebraic Statistics and Latent Tree Models explains how to analyze statistical models with hidden (latent) variables. It takes a;

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Generalized Latent Variable Modeling

This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models;

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Algebraic Statistics

semialgebraic sets. The algebra/statistics connection is now over twenty years old, and this book presents the first broad introductory treatment of the;

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Latent Variable Models and Factor Analysis

Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor analysis and latent variable modeling;

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Latent Variable and Latent Structure Models

traditions: psychometrics and structural equation modeling. Latent Variable and Latent Structure Models' thought-provoking chapters from the leading;

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Latent Variable and Latent Structure Models

traditions: psychometrics and structural equation modeling. Latent Variable and Latent Structure Models' thought-provoking chapters from the leading;

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An Introduction to Latent Class Analysis

This book provides methods and applications of latent class analysis, and the following topics are taken up in the focus of discussion;

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Statistics In The Social Sciences

Fashioned after the 2006 Winemiller Symposium on Recent Advances in Social Science Statistics, and bringing together top researchers from;

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Latent Markov Models for Longitudinal Data

focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models;

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Latent Markov Models for Longitudinal Data

focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models;

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Statistical Models in S

, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the;

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Handbook of Latent Variable and Related Models

among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described;

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Current Topics in the Theory and Application of Latent Variable Models

This book presents recent developments in the theory and application of latent variable models (LVMs) by some of the most prominent;

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Current Topics in the Theory and Application of Latent Variable Models

This book presents recent developments in the theory and application of latent variable models (LVMs) by some of the most prominent;

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An Introduction to Latent Variable Growth Curve Modeling: Concepts, Issues, and Application, Second Edition

then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model;

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An Introduction to Latent Variable Growth Curve Modeling

then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model;

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Latent Variable Models

Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing;

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Latent Variable Models

Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing;

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Advances in Latent Variables

Conference Advances in Latent Variables. Methods, Models and Applications , held at the Department of Economics and Management of the University;

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Advances in Latent Variables

Conference Advances in Latent Variables. Methods, Models and Applications , held at the Department of Economics and Management of the University;

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Geometry of Subanalytic and Semialgebraic Sets

Subanalytic and semialgebraic sets were introduced for topological and systematic investigations of real analytic and algebraic sets. This;

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Latent Class and Latent Transition Analysis

One of the few books on latent class analysis (LCA) and latent transition analysis (LTA) with a comprehensive treatment of longitudinal;

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Bayesian Methods for Management and Business

models including hierarchal models, generalized linear models, and latent variable models are presented to further bridge the theory and;

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The Exploration for Guessing and Latent Ability in IRT Models

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Advances in Latent Variable Mixture Models

latent variable mixture models before the volume moves to more specific constellations of topics. Part I, Multilevel and Longitudinal Systems;

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The EM Algorithm and Related Statistical Models

data problems. The text covers current topics including statistical models with latent variables, as well as neural network models, and Markov;

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