Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics (Statistics for Biology and Health)
Gianola, Daniel,Sorensen, Daniel
ISBN 10: 0387954406 ISBN 13: 9780387954400
Edité par Springer, 2002
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Hardcover
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Synopsis :
This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style and contain much more detail than necessary. Here, an effort has been made to relate biological to statistical parameters throughout, and the book includes extensive examples that illustrate the developing argument.
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Détails bibliographiques
Titre : Likelihood, Bayesian, and MCMC Methods in ...
Éditeur : Springer
Date d'édition : 2002
Reliure : Hardcover
Etat : Good
Edition : 3ème Édition
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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics.
Edité par
New York, Springer, ., 2002
ISBN 10 : 0387954406
ISBN 13 : 9780387954400
Ancien ou d'occasion
Couverture rigide
Vendeur : Universitätsbuchhandlung Herta Hold GmbH, Berlin, Allemagne
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XVII, 740 p. Hardcover Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Corr. 2nd. print. 2004. Stamped. Statistics for Biology and Health. Sprache: Englisch. N° de réf. du vendeur 307GB
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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics (Statistics for Biology and Health)
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Hardcover. Etat : new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks. N° de réf. du vendeur Scanned0387954406
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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
Edité par
Springer New York, 2002
ISBN 10 : 0387954406
ISBN 13 : 9780387954400
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Key background given, including a review of probability and distribution theoryEnables access to the theories for less technically proficient biology and agriculture studentsThe relationship between biological and statistical parameters is . N° de réf. du vendeur 5912532
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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics (Statistics for Biology and Health)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
Edité par
Springer New York, Springer US Aug 2002, 2002
ISBN 10 : 0387954406
ISBN 13 : 9780387954400
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Neuware -Over the last ten years the introduction of computer intensive statistical methods has opened new horizons concerning the probability models that can be fitted to genetic data, the scale of the problems that can be tackled and the nature of the questions that can be posed. In particular, the application of Bayesian and likelihood methods to statistical genetics has been facilitated enormously by these methods. Techniques generally referred to as Markov chain Monte Carlo (MCMC) have played a major role in this process, stimulating synergies among scientists in different fields, such as mathematicians, probabilists, statisticians, computer scientists and statistical geneticists. Specifically, the MCMC 'revolution' has made a deep impact in quantitative genetics. This can be seen, for example, in the vast number of papers dealing with complex hierarchical models and models for detection of genes affecting quantitative or meristic traits in plants, animals and humans that have been published recently.This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Most students in biology and agriculture lack the formal background needed to learn these modern biometrical techniques. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style, and have been written by and addressed to professional statisticians. For this reason, considerable more detail is offered than what may be warranted for a more mathematically apt audience.The book is divided into four parts. Part I gives a review of probability and distribution theory. Parts II and III present methods of inference and MCMC methods. Part IV discusses several models that can be applied in quantitative genetics, primarily from a bayesian perspective.An effort has been made to relate biological to statistical parameters throughout, and examples are used profusely to motivate the developments.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 760 pp. Englisch. N° de réf. du vendeur 9780387954400
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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
Edité par
Springer New York Aug 2002, 2002
ISBN 10 : 0387954406
ISBN 13 : 9780387954400
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Over the last ten years the introduction of computer intensive statistical methods has opened new horizons concerning the probability models that can be fitted to genetic data, the scale of the problems that can be tackled and the nature of the questions that can be posed. In particular, the application of Bayesian and likelihood methods to statistical genetics has been facilitated enormously by these methods. Techniques generally referred to as Markov chain Monte Carlo (MCMC) have played a major role in this process, stimulating synergies among scientists in different fields, such as mathematicians, probabilists, statisticians, computer scientists and statistical geneticists. Specifically, the MCMC 'revolution' has made a deep impact in quantitative genetics. This can be seen, for example, in the vast number of papers dealing with complex hierarchical models and models for detection of genes affecting quantitative or meristic traits in plants, animals and humans that have been published recently. This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Most students in biology and agriculture lack the formal background needed to learn these modern biometrical techniques. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style, and have been written by and addressed to professional statisticians. For this reason, considerable more detail is offered than what may be warranted for a more mathematically apt audience. The book is divided into four parts. Part I gives a review of probability and distribution theory. Parts II and III present methods of inference and MCMC methods. Part IV discusses several models that can be applied in quantitative genetics, primarily from a bayesian perspective.An effort has been made to relate biological to statistical parameters throughout, and examples are used profusely to motivate the developments. 760 pp. Englisch. N° de réf. du vendeur 9780387954400
Quantité disponible : 2 disponible(s)
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Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
Edité par
Springer New York, Springer US, 2002
ISBN 10 : 0387954406
ISBN 13 : 9780387954400
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Over the last ten years the introduction of computer intensive statistical methods has opened new horizons concerning the probability models that can be fitted to genetic data, the scale of the problems that can be tackled and the nature of the questions that can be posed. In particular, the application of Bayesian and likelihood methods to statistical genetics has been facilitated enormously by these methods. Techniques generally referred to as Markov chain Monte Carlo (MCMC) have played a major role in this process, stimulating synergies among scientists in different fields, such as mathematicians, probabilists, statisticians, computer scientists and statistical geneticists. Specifically, the MCMC 'revolution' has made a deep impact in quantitative genetics. This can be seen, for example, in the vast number of papers dealing with complex hierarchical models and models for detection of genes affecting quantitative or meristic traits in plants, animals and humans that have been published recently. This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Most students in biology and agriculture lack the formal background needed to learn these modern biometrical techniques. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style, and have been written by and addressed to professional statisticians. For this reason, considerable more detail is offered than what may be warranted for a more mathematically apt audience. The book is divided into four parts. Part I gives a review of probability and distribution theory. Parts II and III present methods of inference and MCMC methods. Part IV discusses several models that can be applied in quantitative genetics, primarily from a bayesian perspective.An effort has been made to relate biological to statistical parameters throughout, and examples are used profusely to motivate the developments. N° de réf. du vendeur 9780387954400
Quantité disponible : 1 disponible(s)
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LIKELIHOOD BAYESIAN & MCMC METHODS IN Q
Edité par
SPRINGER, 2002
ISBN 10 : 0387954406
ISBN 13 : 9780387954400
Ancien ou d'occasion
Couverture rigide
Vendeur : OM Books, Sevilla, SE, Espagne
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Etat : Usado - bueno. N° de réf. du vendeur 9780387954400
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