Now that we have seen the basics of genetics, we turn to an introduction to the statistical methodologies that we will use throughout this book. Most of the statistical inferences that we will make will be based on likelihood analysis, and we will be concerned not only with constructing the appropriate likelihood function for a given model but also with methods for computing and optimizing the likelihood. We start here with some basics and work our way toward likelihood analysis of a genetic linkage model.


Posterior Distribution Likelihood Function Prior Distribution Maximum Likelihood Estimator Sample Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science + Business Media, LLC 2007

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