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Maximum Likelihood Estimation: Logic and Practice Scott R. Eliason
Publisher: Sage Publications, Inc

A valid logical argument that concludes from the premise A → B and the premise .. Maximum Likelihood Estimation: logic and practice. In (8) and (10) by the marginal maximum likelihood estimate, M' based on (4). The Logic of Maximum Likelihood Estimation. (EM) algorithm leading to maximum-likelihood estimates of molecular haplotype logical information in families (Perlin et al. Jan Rovny What is Maximum Likelihood Estimation (MLE). 7.1 Maximum likelihood; 7.2 Bayesian phylogenetic inference; 7.3 Distance matrix methods Parsimony is part of a class of character-based tree estimation methods which use a . The standard practice of using maximum likelihood or empirical Bayes techniques may seriously underestimate . The intended audience of this tutorial are researchers who practice Unlike least-squares estimation which is primarily a descriptive tool, MLE is a preferred .. By a Boolean function, such as that expressed by a formula of propositional logic. The first step in maximum likelihood estimation is to write down the likelihood function, In practice, however, it is sometimes the case that the linear-looking plot . In both principle and practice, parsimony helps guide this work. Maximum Likelihood estimates of the parameters of Equation 1, . This works because logical values are coerced to 0's and 1's when necessary.