Analysis of Incomplete Multivariate Data

"Overall, the book provides a sound basis on which one can build when dealing with real dataI take pleasure in recommending this well-written text."-Rainer Schlittgen in Statistical Papers"This book provides an excellent introduction to statistical inferenceThanks to the clear and relatively complete treatment of many of the main ideas in this area, even theoretically oriented readers may find this book worthwhile."-Mark Steel, Mathematical Reviews

Autorentext
J.L. Schafer

Klappentext
This work develops simulation techniques based on Bayesian (subjective) inference for multivariate data with missing values.

Zusammenfassung
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 with real data examples, complemented by extended discussions and practical advice.

Inhalt
Introduction Assumptions EM and Inference by Data Augmentation Methods for Normal Data More on the Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed Data Further Topics Appendices References Index

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