739,88 €
822,09 €
-10% with code: EXTRA
Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics
739,88
822,09 €
  • We will send in 10–14 business days.
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, effort has been made to relate biological to statistical parameters throug…
  • Publisher:
  • ISBN-10: 0387954406
  • ISBN-13: 9780387954400
  • Format: 15.7 x 24.6 x 3.9 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

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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, effort has been made to relate biological to statistical parameters throughout, and the book includes extensive examples that illustrate the developing argument. Where most students in biology and agriculture lack the formal background needed to learn these modern biometrical techniques, this text bridges the gap by providing essential background material.

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  • Author: Daniel Sorensen
  • Publisher:
  • ISBN-10: 0387954406
  • ISBN-13: 9780387954400
  • Format: 15.7 x 24.6 x 3.9 cm, hardcover
  • Language: English English

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, effort has been made to relate biological to statistical parameters throughout, and the book includes extensive examples that illustrate the developing argument. Where most students in biology and agriculture lack the formal background needed to learn these modern biometrical techniques, this text bridges the gap by providing essential background material.

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