Displaying similar documents to “Quasi-maximum likelihood estimator of Laplace (1, 1) for GARCH models”

Asymptotic normality in mixture models

Sara Van De Geer (2010)

ESAIM: Probability and Statistics

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We study the estimation of a linear integral functional of a distribution F, using i.i.d. observations which density is a mixture of a family of densities k(.,y) under F. We examine the asymptotic distribution of the estimator obtained by plugging the non parametric maximum likelihood estimator (NPMLE) of F in the functional. A problem here is that usually, the NPMLE does not dominate F.
Our main aim here is to show that this can be overcome by considering a convex combination...

On asymptotics of the maximum likelihood scale invariant estimator of the shape parameter of the gamma distribution

A. Zaigraev, A. Podraza-Karakulska (2008)

Applicationes Mathematicae

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The maximum likelihood scale invariant estimator of the shape parameter of the gamma distribution, proposed by the authors [Statist. Probab. Lett. 78 (2008)], is considered. The asymptotics of the mean square error of this estimator, with respect to that of the usual maximum likelihood estimator, is established.

Robust m-estimator of parameters in variance components model

Roman Zmyślony, Stefan Zontek (2002)

Discussiones Mathematicae Probability and Statistics

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It is shown that a method of robust estimation in a two way crossed classification mixed model, recently proposed by Bednarski and Zontek (1996), can be extended to a more general case of variance components model with commutative a covariance matrices.

Likelihood and quasi - likelihood estimation of transition probabilities

Ewa Bakinowska, Radosław Kala (2004)

Discussiones Mathematicae Probability and Statistics

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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.

Quasi-Likelihood Estimation for Ornstein-Uhlenbeck Diffusion Observed at Random Time Points

Adès, Michel, Dion, Jean-Pierre, MacGibbon, Brenda (2005)

Serdica Mathematical Journal

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2000 Mathematics Subject Classification: 60J60, 62M99. In this paper, we study the quasi-likelihood estimator of the drift parameter θ in the Ornstein-Uhlenbeck diffusion process, when the process is observed at random time points, which are assumed to be unobservable. These time points are arrival times of a Poisson process with known rate. The asymptotic properties of the quasi-likelihood estimator (QLE) of θ, as well as those of its approximations are also elucidated....

Bayesian estimation of AR(1) models with uniform innovations

Hocine Fellag, Karima Nouali (2005)

Discussiones Mathematicae Probability and Statistics

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The first-order autoregressive model with uniform innovations is considered. In this paper, we propose a family of BAYES estimators based on a class of prior distributions. We obtain estimators of the parameter which perform better than the maximum likelihood estimator.