Kaoru Kurosawa: Evolutionary Statistical Procedures : An Evolutionary Computation Approach to Statistical Procedures Designs and Applications - neues Buch
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 l… Mehr…
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.; PDF; Reference & Languages > Sociology & anthropology > Sociology > Social research & statistics, Springer Berlin Heidelberg<
hive.co.uk
No. 9783642162183. Versandkosten:Instock, Despatched same working day before 3pm, zzgl. Versandkosten. Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
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 l… Mehr…
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. eBook Francesco Battaglia#Irene Poli#Roberto Baragona PDF, Springer, 03.01.2011, Springer, 2011<
Thalia.de
Nr. 28850979. Versandkosten:, Sofort per Download lieferbar, DE. (EUR 0.00) Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
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 l… Mehr…
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 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 Electronics > Computers > Tablet Computers, Springer<
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 l… Mehr…
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.; PDF; Reference & Languages > Sociology & anthropology > Sociology > Social research & statistics, Springer Berlin Heidelberg<
No. 9783642162183. Versandkosten:Instock, Despatched same working day before 3pm, zzgl. Versandkosten.
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 l… Mehr…
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. eBook Francesco Battaglia#Irene Poli#Roberto Baragona PDF, Springer, 03.01.2011, Springer, 2011<
Nr. 28850979. Versandkosten:, Sofort per Download lieferbar, DE. (EUR 0.00)
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 l… Mehr…
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 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 Electronics > Computers > Tablet Computers, Springer<
1Da einige Plattformen keine Versandkonditionen übermitteln und diese vom Lieferland, dem Einkaufspreis, dem Gewicht und der Größe des Artikels, einer möglichen Mitgliedschaft der Plattform, einer direkten Lieferung durch die Plattform oder über einen Drittanbieter (Marketplace), etc. abhängig sein können, ist es möglich, dass die von eurobuch angegebenen Versandkosten nicht mit denen der anbietenden Plattform übereinstimmen.
Detailangaben zum Buch - Evolutionary Statistical Procedures
EAN (ISBN-13): 9783642162183 ISBN (ISBN-10): 3642162185 Erscheinungsjahr: 2011 Herausgeber: Springer Berlin 296 Seiten Sprache: eng/Englisch
Buch in der Datenbank seit 2012-01-11T18:24:54+01:00 (Zurich) Detailseite zuletzt geändert am 2023-02-18T20:58:49+01:00 (Zurich) ISBN/EAN: 3642162185
ISBN - alternative Schreibweisen: 3-642-16218-5, 978-3-642-16218-3 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: barag, bara, francesco poli, robert, roberto battaglia, kurosawa Titel des Buches: evolutionary computing, pro evolution
Weitere, andere Bücher, die diesem Buch sehr ähnlich sein könnten:
