Results 151 to 160 of about 1,621,703 (196)

Die Maximum-Likelihood-Methode

1970
Die Verteilung der Zufallsvariablen X hange von einem unbekannten Parameter θ ab. θ gehore zu einer Menge Ω von Parametern.- Die Wahrscheinlichkeitsdichte f(x,θ) ist eine Funktion mit dem Stichprobenraum ae als Definitionsmenge und ℝ als Wertmenge. Fast man sie aber bei festgehaltenem x als Funktion mit der Parametermenge Ω als Definitionsmenge auf, so
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Bayes and Maximum Likelihood Methods

2010
While the parameter estimation methods presented so far assumed that the parameters θ and the observations of the output y are deterministic values, the parameters themselves and/or the output will now be seen in a stochastic view as a series of random variables.
Rolf Isermann, Marco Münchhof
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Phylogenetic Inference: Maximum Likelihood Methods

2000
Abstract The idea of using a maximum likelihood (ML) method for phylogenetic inference was first presented by Cavalli-Sforza and Edwards (1967) for gene frequency data, but they encountered a number of problems in implementing the method.
Masatoshi Nei, Sudhir Kumar
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Methods for maximum-likelihood deconvolution

Journal of the Optical Society of America A, 1996
An alternative approach to the maximum-likelihood solution of deconvolution problems is presented. The resulting algorithms are faster converging than the conventional Richardson–Lucy and clean algorithms, as well as being more flexible when one is dealing with different types of noise.
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The method of maximum likelihood

1998
Abstract 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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Magnetic resonance linear accelerator technology and adaptive radiation therapy: An overview for clinicians

Ca-A Cancer Journal for Clinicians, 2022
William A Hal, X Allen Li, Daniel A Low
exaly  

The Method of Maximum Likelihood

1999
In 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

1997
Publisher 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“

2013
Wir 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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9 Maximum Likelihood Methods

2022
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