{"product_id":"likelihood-bayesian-and-mcmc-methods-in-quantitative-genetics-statistics-for-biology-and-health-9780387954400","title":"Likelihood  Bayesian  and MCMC Methods in Quantitative Genetics (Statistics for Biology and Health)","description":"\u003cp\u003eOver 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.\u003c\/p\u003e","brand":"My Store","offers":[{"title":"Default Title","offer_id":45651461374005,"sku":"ByrdShop_0387954406","price":320.62,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0627\/8139\/0901\/files\/9780387954400.jpg?v=1781834885","url":"https:\/\/atxbooks.com\/products\/likelihood-bayesian-and-mcmc-methods-in-quantitative-genetics-statistics-for-biology-and-health-9780387954400","provider":"ATX Books","version":"1.0","type":"link"}