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The method of maximum likelihood
1998Abstract Consider a random variable x distributed according to a p.d.f. f(x; θ). Suppose the functional form of f(x; θ) is known, but the value of at least one parameter θ (or parameters θ = (θ 1, … , θ m)) are not known. That is, f ( x; θ) represents a composite hypothesis for the p.d.f. (cf. Section 4.1).
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The Method of Maximum Likelihood
1999In the last chapter we introduced the concept of parameter estimation. We have also described the desirable properties of estimators, though without specifying how such estimators can be constructed in a particular case. We have derived estimators only for the important quantities expectation value and variance. We now take on the general problem.
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14 Nonparametric maximum likelihood methods
1997Publisher Summary This chapter discusses nonparametric maximum likelihood methods. The nonparametric maximum likelihood (NPML) method is a direct attack, via the likelihood principle, on the problem of dealing with an unknown distribution function in estimation or testing.
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Die Methode der „Maximum Likelihood“
2013Wir hatten uns bereits im letzten Kapitel mit dem Problem der Schatzung der Parameter einer Verteilung durch Stichproben beschaftigt und dabei die wunschenswerten Eigenschaften von Schatzfunktionen diskutiert, ohne jedoch eine Vorschrift anzugeben, wie man im Einzelfall solche Schatzfunktionen findet.
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PHYLOGENY ESTIMATION AND HYPOTHESIS TESTING USING MAXIMUM LIKELIHOOD
Annual Review of Ecology, Evolution, and Systematics, 1997John P Huelsenbeck, Keith A Crandall
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A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
Systematic Biology, 2003Stephane Guindon, Olivier Gascuel
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IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies
Molecular Biology and Evolution, 2015Lam-Tung Nguyen +2 more
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