Likelihood bayesian mcmc methods de gianola daniel (14 resultados)
Idioma: Inglés
Editorial: Springer, 2002
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Librería: Orion Tech, Kingwood, TX, Estados Unidos de AmericaOrion Tech
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EUR 80,06
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hardcover. Condición: Fair.
Idioma: Inglés
Editorial: Springer, 2002
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Librería: ThriftBooks-Dallas, Dallas, TX, Estados Unidos de AmericaThriftBooks-Dallas
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EUR 80,07
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Hardcover. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.
Idioma: Inglés
Editorial: Springer, 2002
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Librería: Wonder Book, Frederick, MD, Estados Unidos de AmericaWonder Book
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EUR 90,73
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Condición: Good. Good condition. 3rd edition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.
Idioma: Inglés
Editorial: Springer, 2002
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Librería: Solr Books, Lincolnwood, IL, Estados Unidos de AmericaSolr Books
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EUR 88,31
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Condición: very_good. This book is in Very good condition. There may be a few flaws like shelf wear and some light wear.
Idioma: Inglés
Editorial: Springer, 2002
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 193,70
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Condición: Used. pp. 764.
Idioma: Inglés
Editorial: Springer, 2002
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 208,73
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Condición: Used. pp. 764.
Idioma: Inglés
Editorial: Springer, 2002
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 349,35
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 401,09
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Taschenbuch. Condición: 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 que…stions 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.
Editorial: Springer, 2002
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Librería: HPB-Red, Dallas, TX, Estados Unidos de AmericaHPB-Red
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EUR 84,15
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Hardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 311,76
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Condición: 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 sta…tistical parameters is .
Idioma: Inglés
Editorial: Springer New York, 2002
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Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 311,76
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Gebunden. Condición: 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 biologic…al and statistical parameters is .
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 374,49
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Taschenbuch. Condición: 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 n…ature 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. 764 pp. Englisch.
Idioma: Inglés
Editorial: Springer New York Aug 2002, 2002
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- Impresión bajo demanda
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 374,49
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: 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 o…f 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.
