Displaying similar documents to “Asymptotic normality and efficiency of two Sobol index estimators”

Asymptotic normality and efficiency of variance components estimators with high breakdown points

Christine H. Müller (2000)

Discussiones Mathematicae Probability and Statistics

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For estimating the variance components of a one-way random effect model recently Uhlig (1995, 1997) and Lischer (1996) proposed non-iterative estimators with high breakdown points. These estimators base on the high breakdown point scale estimators of Rousseeuw and Croux (1992, 1993), which they called Q-estimators. In this paper the asymptotic normal distribution of the new variance components estimators is derived so that the asymptotic efficiency of these estimators can be compared...

Minimum disparity estimators for discrete and continuous models

María Luisa Menéndez, Domingo Morales, Leandro Pardo, Igor Vajda (2001)

Applications of Mathematics

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Disparities of discrete distributions are introduced as a natural and useful extension of the information-theoretic divergences. The minimum disparity point estimators are studied in regular discrete models with i.i.d. observations and their asymptotic efficiency of the first order, in the sense of Rao, is proved. These estimators are applied to continuous models with i.i.d. observations when the observation space is quantized by fixed points, or at random, by the sample quantiles...

The use of third-order moments in structural models.

Erik Meijer, Ab Mooijart (1994)

Qüestiió

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Structural models are usually estimated using only second order moments (covariances or correlations). When variables are nor multivariate normally distributed, however, methods that also fit higher order moments, such as skewnesses, are theoretically asymptotically preferable. This article reports result from a Monte Carlo simulation study in which estimators that fit both second-order moments and third-order moments are compared with estimators that fit only second-order moments. ...

Comparison at optimal levels of classical tail index estimators: a challenge for reduced-bias estimation?

M. Ivette Gomes, Lígia Henriques-Rodrigues (2010)

Discussiones Mathematicae Probability and Statistics

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In this article, we begin with an asymptotic comparison at optimal levels of the so-called "maximum likelihood" (ML) extreme value index estimator, based on the excesses over a high random threshold, denoted PORT-ML, with PORT standing for peaks over random thresholds, with a similar ML estimator, denoted PORT-MP, with MP standing for modified-Pareto. The PORT-MP estimator is based on the same excesses, but with a trial of accommodation of bias on the Generalized Pareto model underlying...

An asymptotically unbiased moment estimator of a negative extreme value index

Frederico Caeiro, M. Ivette Gomes (2010)

Discussiones Mathematicae Probability and Statistics

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In this paper we consider a new class of consistent semi-parametric estimators of a negative extreme value index, based on the set of the k largest observations. This class of estimators depends on a control or tuning parameter, which enables us to have access to an estimator with a null second-order component of asymptotic bias, and with a rather interesting mean squared error, as a function of k. We study the consistency and asymptotic normality of the proposed estimators. Their finite...

Efficiency rate and local deficiency of Huber's location estimators and of the α-estimators.

Asunción Rubio, Jan Amos Visek (1991)

Trabajos de Estadística

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The paper studies the problem of selecting an estimator with (approximately) minimal asymptotic variance. For every fixed contamination level there is usually just one such estimator in the considered family. Using the first and the second derivative of the asymptotic variance with respect to the parameter which parametrizes the family of estimators the paper gives two examples of how to select the estimator and gives an approximation to a loss which we suffer when we use the estimator...