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Wyszukujesz frazę "likelihood estimation" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Likelihood and quasi - likelihood estimation of transition probabilities
Autorzy:
Bakinowska, Ewa
Kala, Radosław
Powiązania:
https://bibliotekanauki.pl/articles/729736.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:
likelihood estimation
quasi-likelihood estimation
transition probabilities
quasi-information matrix
Opis:
In the paper two approaches to the problem of estimation of transition probabilities are considered. The approach by McCullagh and Nelder [5], based on the independent model and the quasi-likelihood function, is compared with the approach based on the marginal model and the standard likelihood function. The estimates following from these two approaches are illustrated on a simple example which was used by McCullagh and Nelder.
Źródło:
Discussiones Mathematicae Probability and Statistics; 2004, 24, 1; 77-84
1509-9423
Pojawia się w:
Discussiones Mathematicae Probability and Statistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
MLE for the γ-order Generalized Normal Distribution
Autorzy:
Kitsos, Christos
Vassiliadis, Vassilios
Toulias, Thomas
Powiązania:
https://bibliotekanauki.pl/articles/729734.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:
γ-order Normal distribution
cumulative distribution
truncated distribution
hazard rate
Maximum likelihood estimation
Opis:
The introduced three parameter (position μ, scale ∑ and shape γ) multivariate generalized Normal distribution (γ-GND) is based on a strong theoretical background and emerged from Logarithmic Sobolev Inequalities. It includes a number of well known distributions such as the multivariate Uniform, Normal, Laplace and the degenerated Dirac distributions. In this paper, the cumulative distribution, the truncated distribution and the hazard rate of the γ-GND are presented. In addition, the Maximum Likelihood Estimation (MLE) method is discussed in both the univariate and multivariate cases and asymptotic results are presented.
Źródło:
Discussiones Mathematicae Probability and Statistics; 2014, 34, 1-2; 143-158
1509-9423
Pojawia się w:
Discussiones Mathematicae Probability and Statistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adaptive trimmed likelihood estimation in regression
Autorzy:
Bednarski, Tadeusz
Clarke, Brenton
Schubert, Daniel
Powiązania:
https://bibliotekanauki.pl/articles/729910.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:
trimmed likelihood estimator
adaptive estimation
regression
Opis:
In this paper we derive an asymptotic normality result for an adaptive trimmed likelihood estimator of regression starting from initial high breakdownpoint robust regression estimates. The approach leads to quickly and easily computed robust and efficient estimates for regression. A highlight of the method is that it tends automatically in one algorithm to expose the outliers and give least squares estimates with the outliers removed. The idea is to begin with a rapidly computed consistent robust estimator such as the least median of squares (LMS) or least trimmed squares (LTS) or for example the more recent MM estimators of Yohai. Such estimators are now standard in statistics computing packages, for example as in SPLUS or R. In addition to the asymptotics we provide data analyses supporting the new adaptive approach. This approach appears to work well on a number of data sets and is quicker than the related brute force adaptive regression approach described in Clarke (2000). This current approach builds on the work of Bednarski and Clarke (2002) which considered the asymptotics for the location estimator only.
Źródło:
Discussiones Mathematicae Probability and Statistics; 2010, 30, 2; 203-219
1509-9423
Pojawia się w:
Discussiones Mathematicae Probability and Statistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On some properties of ML and REML estimators in mixed normal models with two variance components
Autorzy:
Gnot, Stanisław
Michalski, Andrzej
Urbańska-Motyka, Agnieszka
Powiązania:
https://bibliotekanauki.pl/articles/729742.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Zielonogórski. Wydział Matematyki, Informatyki i Ekonometrii
Tematy:
mixed linear models
likelihood-based inference
ML- and REML- estimation
variance components
Fisher's information
Opis:
In the paper, the problem of estimation of variance components σ₁² and σ₂² by using the ML-method and REML-method in a normal mixed linear model {Y,E(Y) = Xβ, Cov(Y) = σ₁²V + σ₂²Iₙ} is considered. This paper deal with properties of estimators of variance components, particularly when an explicit form of these estimators is unknown. The conditions when the ML and REML estimators can be expressed in explicit forms are given, too. The simulation study for one-way classification unbalanced random model together with a new proposition of approximation of expectation and variances of ML and REML estimators are shown. Numerical calculations with reference to the generalized Fisher's information are also given.
Źródło:
Discussiones Mathematicae Probability and Statistics; 2004, 24, 1; 109-126
1509-9423
Pojawia się w:
Discussiones Mathematicae Probability and Statistics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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