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Evolutionary Statistical Procedures - Roberto Baragona#Francesco Battaglia#Irene Poli
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Evolutionary Statistical Procedures - neues Buch

ISBN: 9783642162176

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This book offers a solid introduction to evolutionary computation for use in applied statistics research. It guides readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods. pThis 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./p Bücher / Fremdsprachige Bücher / Englische Bücher 978-3-642-16217-6, Springer

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Evolutionary Statistical Procedures - Roberto Baragona#Francesco Battaglia#Irene Poli
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Roberto Baragona#Francesco Battaglia#Irene Poli:

Evolutionary Statistical Procedures - neues Buch

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pThis 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./p This book offers a solid introduction to evolutionary computation for use in applied statistics research. It guides readers through the crucial issues of optimization problems in statistical settings and the implementation of tailored methods. Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher, Springer

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Evolutionary Statistical Procedures - Roberto Baragona
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[ED: Buch], [PU: Springer-Verlag GmbH], Neuware - 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., [SC: 0.00], Neuware, gewerbliches Angebot, FixedPrice, [GW: 622g]

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Evolutionary Statistical Procedures: An Evolutionary Computation Approach to Statistical Procedures Designs and Applications - Baragona, Roberto / Battaglia, Francesco / Poli, Irene
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The proposed text offers a solid 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 in the process of solving increasingly complex problems in high dimensions and its methodology is now being generalized to parameters whose estimators do not follow mathematically simple distributions. Many of these challenges involve optimizing functions for which analytic solutions are not feasible. Evolutionary algorithms present 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 methods). Evolutionary Statistical Procedures: An Evolutionary Computation Approach to Statistical Procedures Designs and Applications Baragona, Roberto / Battaglia, Francesco / Poli, Irene, Springer

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Baragona, Roberto; Battaglia, Francesco; Poli, Irene:
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2011, ISBN: 3642162177

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Details zum Buch
Evolutionary Statistical Procedures
Autor:

Baragona, Roberto; Battaglia, Francesco; Poli, Irene

Titel:

Evolutionary Statistical Procedures

ISBN-Nummer:

9783642162176

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.

Detailangaben zum Buch - Evolutionary Statistical Procedures


EAN (ISBN-13): 9783642162176
ISBN (ISBN-10): 3642162177
Gebundene Ausgabe
Erscheinungsjahr: 2011
Herausgeber: Springer-Verlag GmbH
276 Seiten
Gewicht: 0,622 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 09.11.2008 10:27:19
Buch zuletzt gefunden am 06.10.2016 08:28:46
ISBN/EAN: 9783642162176

ISBN - alternative Schreibweisen:
3-642-16217-7, 978-3-642-16217-6

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