Articles liés à Analysis of Incomplete Multivariate Data
Synopsis
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 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.
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J.L. Schafer
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Analysis of Incomplete Multivariate Data (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
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CRC Press, 2023
ISBN 10 : 1032477997
ISBN 13 : 9781032477992
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Analysis of Incomplete Multivariate Data
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ISBN 13 : 9781032477992
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Analysis of Incomplete Multivariate Data
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Chapman and Hall/CRC, 2023
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ISBN 13 : 9781032477992
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Analysis of Incomplete Multivariate Data
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Analysis of Incomplete Multivariate Data
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Taylor & Francis, CRC Press, 2023
ISBN 10 : 1032477997
ISBN 13 : 9781032477992
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 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. 444 pp. Englisch. N° de réf. du vendeur 9781032477992
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Analysis of Incomplete Multivariate Data
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Chapman and Hall/CRC, 2023
ISBN 10 : 1032477997
ISBN 13 : 9781032477992
Neuf
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Analysis of Incomplete Multivariate Data
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. J.L. SchaferThe 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 tool. N° de réf. du vendeur 801266747
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Analysis of Incomplete Multivariate Data
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Analysis of Incomplete Multivariate Data
Edité par
Taylor & Francis, Chapman And Hall/CRC, 2023
ISBN 10 : 1032477997
ISBN 13 : 9781032477992
Neuf
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 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. N° de réf. du vendeur 9781032477992
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Analysis of Incomplete Multivariate Data (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
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