Analysis of Incomplete Multivariate Data - Info and Reading Options
By Joseph L. Schafer
"Analysis of Incomplete Multivariate Data" was published by Chapman & Hall/CRC in August 1, 1997 - Boca Raton, Fla., the book is classified in Mathematics genre, it has 448 pages and the language of the book is English.
“Analysis of Incomplete Multivariate Data” Metadata:
- Title: ➤ Analysis of Incomplete Multivariate Data
- Author: Joseph L. Schafer
- Language: English
- Number of Pages: 448
- Is Family Friendly: Yes - No Mature Content
- Publisher: Chapman & Hall/CRC
- Publish Date: August 1, 1997
- Publish Location: Boca Raton, Fla.
- Genres: Mathematics
“Analysis of Incomplete Multivariate Data” Subjects and Themes:
- Subjects: Multivariate analysis - Statistics - MEDICAL / Biostatistics - Analyse multivariée
Edition Identifiers:
- Google Books ID: MdKangEACAAJ
- The Open Library ID: OL7478158M - OL8086972W
- Online Computer Library Center (OCLC) ID: 123486463 - 37594064
- Library of Congress Control Number (LCCN): gb97054849
- ISBN-13: 9780412040610
- ISBN-10: 0412040611
- All ISBNs: 0412040611 - 9780412040610
AI-generated Review of “Analysis of Incomplete Multivariate Data”:
Snippets and Summary:
This book presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical or both.
This book presents methods of statistical inference from multivariate datasets with missing values where missingness may occur on any or all of the variables.
"Analysis of Incomplete Multivariate Data" Description:
Google Books:
This book presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical or both. It is written for applied statisticians, biostatisticians, practitioners of sample surveys, graduate students and other methodologically-oriented researchers in search of practical tools to handle missing data. The focus is applied rather than theoretical, but technical details have been included where necessary to help readers thoroughly understand the statistical properties of these methods and the behavior of the accompanying algorithms. All techniques are illustrated with real data examples, with extended discussion and practical advice.
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