Evolutionary Statistical Procedures

By: and and

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Synopsis
This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions are infeasible. Evolutionary algorithms represent a powerful and easily understood means of approximating the optimum value in a variety of settings. The proposed text seeks to guide readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods (including both stand-alone evolutionary algorithms and hybrid crosses of these procedures with standard statistical algorithms like Metropolis-Hastings) in a variety of applications. This book would serve as an excellent reference work for statistical researchers at an advanced graduate level or beyond, particularly those with a strong background in computer science.
Copyright:
2010

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9783642162183
Related ISBNs:
9783642162176
Publisher:
Springer Berlin Heidelberg
Date of Addition:
Copyrighted By:
Springer
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Social Studies, Mathematics and Statistics, Medicine
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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