Evolutionary Statistical Procedures

Author/creator Baragona, Roberto Author
Other author Battaglia, Francesco Author
Other author Poli, Irene Author
Format Electronic
Publication InfoNew York : Springer
Descriptioniv, 296 p. ill 23.500 x 015.500 cm.
Supplemental ContentFull text available from Springer Nature - Springer Mathematics and Statistics eBooks 2011 English International
Supplemental ContentFull text available from Springer Books
Subjects

SeriesStatistics and Computing Ser.
Summary Annotation 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.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
ISBN9783642162176
ISBN3642162177 (Trade Cloth) Active Record
Standard identifier# 9783642162176
Stock number3642162177 00024965