Author: J.L. Schafer
Edition: 1
Publisher: Chapman and Hall/CRC
Binding: Hardcover
ISBN: 0412040611
Analysis of Incomplete Multivariate Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
The last two decades have seen enormous developments in statistical methods for incomplete data. Medical books Analysis of Incomplete Multivariate Data . The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values on a routine basis.
Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical, or both Medical books Analysis of Incomplete Multivariate Data, 9780412040610. Analysis of Incomplete Multivariate Data, ISBN-13: 9780412040610, ISBN-10: 0412040611
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Analysis of Incomplete Multivariate Data, ISBN-13: 9780412040610, ISBN-10: 0412040611
Store Search search Title, ISBN and Author Analysis of Incomplete Multivariate Data by JL Schafer Estimated delivery 3-12 business days Format Hardcover Condition Brand New The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those develo
author jl schafer format hardback language english publication year 01 08 1997 series chapman hall crc monographs on statistics applied probability subject mathematics sciences subject 2 mathematics title analysis of incomplete multivariate data author cox dr series edited by reid n series edited by isham valerie series edited by louis thomas a series edited by tong howell series edited by keiding niels series edited by schafer jl author publisher chapman hall publication date dec 01 1997 pag
The last two decades have seen enormous developments in statistical methods for incomplete data. Yet in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values. Analysis of Incomplete Multivariate Data helps to bridge the gap between theory and practice and makes these missing-data tools accessible to a broad audience. The author focuses on applications, as necessary, to help readers thoroughly understand the statistical properties of the methods and the behavior of the accompanying algorithms. All techniques are illustrated w
Medical Book Analysis of Incomplete Multivariate Data
The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values on a routine basis.
Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical, or both. The focus is applied, where necessary, to help readers thoroughly understand the statistical properties of those methods, and the behavior of the accompanying algorithms.
All techniques are illustrated with real data examples, with extended discussion and practical advice. All of the algorithms described in this book have been implemented by the author for general use in the statistical languages S and S Plus. The software is available free of charge on the Internet.
