Displaying similar documents to “On robust estimation in the simplest exponential model”

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...

Estimating quantiles with Linex loss function. Applications to VaR estimation

Ryszard Zieliński (2005)

Applicationes Mathematicae

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Sometimes, e.g. in the context of estimating VaR (Value at Risk), underestimating a quantile is less desirable than overestimating it, which suggests measuring the error of estimation by an asymmetric loss function. As a loss function when estimating a parameter θ by an estimator T we take the well known Linex function exp{α(T-θ)} - α(T-θ) - 1. To estimate the quantile of order q ∈ (0,1) of a normal distribution N(μ,σ), we construct an optimal estimator in the class of all estimators...

Unbiased estimation of reliability for two-parameter exponential distribution under time censored sampling

S. Sengupta (2010)

Applicationes Mathematicae

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The problem considered is that of unbiased estimation of reliability for a two-parameter exponential distribution under time censored sampling. We give necessary and sufficient conditions for the existence of uniformly minimum variance unbiased estimator and also provide a characterization of a complete class of unbiased estimators in situations where unbiased estimators exist.

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...

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. ...

On non-existence of moment estimators of the GED power parameter

Bartosz Stawiarski (2016)

Discussiones Mathematicae Probability and Statistics

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We reconsider the problem of the power (also called shape) parameter estimation within symmetric, zero-mean, unit-variance one-parameter Generalized Error Distribution family. Focusing on moment estimators for the parameter in question, through extensive Monte Carlo simulations we analyze the probability of non-existence of moment estimators for small and moderate samples, depending on the shape parameter value and the sample size. We consider a nonparametric bootstrap approach and prove...