Showing posts with label Generalized. Show all posts
Showing posts with label Generalized. Show all posts

Thursday, 12 May 2016

Generalized Latent Variable Modeling

Generalized Latent Variable Modeling
By:"Anders Skrondal","Sophia Rabe-Hesketh"
Published on 2004-05-11 by CRC Press

This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics. They present exciting and realistic applications that demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. The examples considered include many nonstandard response types, such as ordinal, nominal, count, and survival data. Joint modeling of mixed responses, such as survival and longitudinal data, is also illustrated. Numerous displays, figures, and graphs make the text vivid and easy to read. About the authors: Anders Skrondal is Professor and Chair in Social Statistics, Department of Statistics, London School of Economics, UK Sophia Rabe-Hesketh is a Professor of Educational Statistics at the Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA.

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ISBN-10:0203489438

ISBN-13:9780203489437


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This Book was ranked 27 by Google Books for keyword Models.

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Sunday, 6 December 2015

Generalized Additive Models

Generalized Additive Models
By:"T.J. Hastie","R.J. Tibshirani"
Published on 1990-06-01 by CRC Press

This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linear assumption of many standard models and allow analysts to uncover structure in the data that might otherwise have been missed. While McCullagh and Nelder's Generalized Linear Models shows how to extend the usual linear methodology to cover analysis of a range of data types, Generalized Additive Models enhances this methodology even further by incorporating the flexibility of nonparametric regression. Clear prose, exercises in each chapter, and case studies enhance this popular text.

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ISBN-10:0412343908

ISBN-13:9780412343902


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This Book was ranked 29 by Google Books for keyword Models.

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