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Chapman and Hall/CRC Analysis of Incomplete Multivariate Data - Chapman & Hall/CRC

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£171.99 £71.04 £93.07 £115.09 £137.12 £159.14 £181.17 25 July 2026 16 August 2026 07 September 2026 29 September 2026 22 October 2026
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Description

This comprehensive monograph bridges the gap between advanced statistical theory and practical data analysis by making missing-data methods accessible to professionals across disciplines. The book explores the EM algorithm and its extensions, multiple imputation techniques, and Markov Chain Monte Carlo approaches, providing flexible and reliable tools for tackling incomplete multivariate datasets. Developed over two decades of statistical research, these methods address the fundamental challenge that most data analysts face when handling missing values routinely. Whether you work in healthcare, research, or data science, this Chapman and Hall/CRC publication equips you with proven strategies to manage incomplete data effectively, moving beyond basic deletion methods to sophisticated inference techniques that preserve statistical integrity and extract maximum insight from your datasets.

Key Features

Covers EM algorithm and its extensions as practical tools for solving incomplete data problems in multivariate analysis.

Explores multiple imputation methods that provide flexible approaches to handling missing values in large datasets.

Presents Markov Chain Monte Carlo techniques for reliable inference when data is incomplete or sparse.

Published by Chapman and Hall/CRC as part of their respected Monographs on Statistics and Applied Probability series.

Designed for data analysts and practitioners who need to apply advanced missing-data methods to real-world problems.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
01 August 1997
Listed Since
08 February 2007

Barcode

No barcode data available

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