Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 103,62
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 103,63
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 102,45
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 102,45
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 121,32
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 111,03
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 111,03
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Publicado por Springer Berlin Heidelberg, 2013
ISBN 10: 3642266541 ISBN 13: 9783642266546
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Publicado por Springer Berlin Heidelberg, 2011
ISBN 10: 3642162177 ISBN 13: 9783642162176
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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).
Librería: Revaluation Books, Exeter, Reino Unido
EUR 151,71
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Añadir al carritoPaperback. Condición: Brand New. 2011 edition. 288 pages. 9.25x6.10x0.67 inches. In Stock.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 153,27
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Añadir al carritoHardcover. Condición: Brand New. 300 pages. 9.00x6.25x0.75 inches. In Stock.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 199,55
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Añadir al carritoCondición: As New. Unread book in perfect condition.