Evolutionary Statistical Procedures (Record no. 9020)

MARC details
000 -LEADER
fixed length control field 02345nam a2200289Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250716115727.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220909b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642162176
040 ## - CATALOGING SOURCE
Original cataloging agency CSL
Language of cataloging eng
Transcribing agency CSL
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
084 ## - COLON CLASSIFICATION NUMBER
Classification number B28 Q1 TB
Assigning agency CSL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Baragona, Roberto
Relator term author.
9 (RLIN) 815713
245 #0 - TITLE STATEMENT
Title Evolutionary Statistical Procedures
Remainder of title : Evolutionary Computation Approach to Statistical Procedures Designs and Applications
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. London :
Name of publisher, distributor, etc. Springer,
Date of publication, distribution, etc. 2011.
300 ## - PHYSICAL DESCRIPTION
Extent xi, 276p.
490 ## - SERIES STATEMENT
Series statement Statistics and Computing
500 ## - GENERAL NOTE
General note Includes References 261-272p.; Index 273-276p.
520 ## - SUMMARY, ETC.
Summary, etc. 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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computational approach.
9 (RLIN) 815714
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Statistical proceedures.
9 (RLIN) 815715
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Mathematics.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Battaglia, Francesco
Relator term co-author.
9 (RLIN) 815716
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Poli, Irene
Relator term co-author.
9 (RLIN) 815717
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Classification part B28, Q1 TB
Koha item type Textual
Source of classification or shelving scheme Colon Classification (CC)
Suppress in OPAC No
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
        Central Science Library Central Science Library 2022-09-12 1031, 30/03/2012, Total Books India   B28 Q1 TB SL1558041 2022-09-12 2022-09-12 Textual
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