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Numerical issues in statistical computing for the social scientist

At last--a social scientist's guide through the pitfalls of modern statistical computing. Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to p...

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Bibliographic Details
Main Authors: Altman, Micah
Group Author: Gill, Jeff; McDonald, Michael, 1967
Published:
Literature type: Electronic eBook
Language: English
Series: Wiley series in probability and statistics
Subjects:
Statistics > Data processing
Social sciences > Statistical methods > Data processing
MATHEMATICS > Probability & Statistics > General
Computational and graphical statistics > General introductory social science > Social sciences special topics.
Electronic books
Online Access: http://onlinelibrary.wiley.com/book/10.1002/0471475769
Summary: At last--a social scientist's guide through the pitfalls of modern statistical computing. Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate inference
Carrier Form: 1 online resource (xv, 331 pages) : illustrations.
Bibliography: Includes bibliographical references and indexes.
ISBN: 9780471475767
0471475769
9780471475743
0471475742
Index Number: QA276
CLC: C32
Contents: Contents -- Preface -- 1. Introduction: Consequences of Numerical Inaccuracy -- 2. Sources of Inaccuracy in Statistical Computation -- 3. Evaluating Statistical Software -- 4. Robust Inference -- 5. Numerical Issues in Markov Chain Monte Carlo Estimation -- 6. Numerical Issues Involved in Inverting Hessian Matrices -- 7. Numerical Behavior of King's EI Method -- 8. Some Details of Nonlinear Estimation -- 9. Spatial Regression Models -- 10. Convergence Problems in Logistic Regression -- 11. Recommendations for Replication and Accurate Analysis -- Bibliography.

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