Numerical Issues in Statistical Computing for the Social Scientist (eBook)

MICAH ALTMAN is Associate Director of the Harvard-MIT Data Center in Cambridge, Massachusetts. JEFF GILL is Associate Professor of Political Science at the University of California, Davis. MICHAEL P. McDONALD is Assistant Professor of Government and Politics at George Mason University in Fairfax, Virginia.

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 Hessian Matrices (Jeff Gill& Gary King).

7. Numerical Behavior of King's EI Method.

8. Some Details of Nonlinear Estimation (B. D. McCullough).

9. Spatial Regression Models (James P. LeSage).

10. Convergence Problems in Logistic Regression (PaulAllison).

11. Recommendations for Replication and AccurateAnalysis.

Bibliography.

Author Index.

Subject Index.

"Uniquely accessible and abounding in modern-day tools, tricks, and
advice, the text successfully bridges the gap between the current
level of social science methodology and the more sophisticated
technical coverage." (Zentralblatt Math 1130, May 2008)

"Clarity of presentations is excellent. Applied statisticians
and computer scientists will like this book and find it very
useful." (Journal of Statistical Computation and Simulation,
November 2005)

"[The authors] ...have succeeded in providing...a good
understanding of the potential pitfalls involved in the
implementation of methodology computationally, and...good advice on
dealing with the problems that can arise." (Statistics in
Medical Research, June 2005)

"This book provides the researcher with an overview of the
issues involved in the implementation and computation of common
statistical procedures...." (Statistical Methods in
Medical Research, Vol. 14, 2005)

"...this book is a good reference for social scientists that
are involved in computational statistics." (Journal of
Statistical Software, April 2005)

"...timely and interesting, and on the whole provides a good
balance of theory, application, and computation."
(Technometrics, May 2005)

"...an excellent text. It has the potential to be enormously
influential across the social sciences...It should be required
reading for everyone who performs statistical computing at the
advanced level..." (Journal of the American Statistical
Association, June 2005)

"...a compact guide to the voluminous literature on
optimisation, numerical analysis, and computational statistics.
This is no small achievement." (Statistical Software
Newsletter in Computational Statistics and Data Analysis)

"...a very important one for researchers, social scientists,
and...graduate and post-graduate students in various
disciplines..." (Computing Reviews.com, July 6, 2004)

"This comprehensive research and guidebook by Altman, Gill, and
McDonald offers to social scientists modern tools and tricks
previously lacking in other works." (Choice, June
2004, Vol. 41 No. 10)