On robust estimation in the simplest exponential model
R. Zieliński, W. Zieliński (1984)
Applicationes Mathematicae
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R. Zieliński, W. Zieliński (1984)
Applicationes Mathematicae
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Ryszard Zieliński (2007)
Applicationes Mathematicae
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It turns out that for standard kernel estimators no inequality like that of Dvoretzky-Kiefer-Wolfowitz can be constructed, and as a result it is impossible to answer the question of how many observations are needed to guarantee a prescribed level of accuracy of the estimator. A remedy is to adapt the bandwidth to the sample at hand.
Irena Wistuba (1983)
Applicationes Mathematicae
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Álex Costa, Albert Satorra, Eva Ventura (2003)
SORT
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This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within area variance and squared bias and one that uses area-specific estimates of variance and squared bias. In the study with real population, we found...
Jaromír Antoch, Marie Husková (2000)
Discussiones Mathematicae Probability and Statistics
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The purpose of this paper is to study Bayesian like R- and M-estimators of change point(s). These estimators have smaller variance than the related argmax type estimators. Confidence intervals for the change point based on the exchangeability arguments are constructed. Finally, theoretical results are illustrated on the real data set.
M.A. Beg (1982)
Metrika
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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...
Ryszard Zieliński (2003)
Applicationes Mathematicae
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If θ ∈ Θ is an unknown real parameter of a given distribution, we are interested in constructing an exactly median-unbiased estimator θ̂ of θ, i.e. an estimator θ̂ such that a median Med(θ̂ ) of the estimator equals θ, uniformly over θ ∈ Θ. We shall consider the problem in the case of a fixed sample size n (nonasymptotic approach).
I. Malinowska, P. Pawlas, D. Szynal (2005)
Applicationes Mathematicae
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The minimum variance linear unbiased estimators (MVLUE), the best linear invariant estimators (BLIE) and the maximum likelihood estimators (MLE) based on m selected kth record values are presented for the parameters of the Gumbel and Burr distributions.
HousiLA P. SINGH AND M. RUIZ ESPEJO (1999)
Revista de la Real Academia de Ciencias Exactas Físicas y Naturales
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M. Dalabehera, L. N. Sahoo (1994)
Qüestiió
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In this paper, we compare six almost unbiased ratio estimators with respect to bias and efficiency for (i) finite populations, and (ii) infinite populations in which the joint distribution of the characters under study is bivariate normal.
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...
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...
Jadwiga Kicinska-Slaby (1982)
Trabajos de Estadística e Investigación Operativa
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Lehmann in [4] has generalised the notion of the unbiased estimator with respect to the assumed loss function. In [5] Singh considered admissible estimators of function λ-r of unknown parameter λ of gamma distribution with density f(x|λ, b) = λb-1 e-λx xb-1 / Γ(b), x>0, where b is a known parameter, for loss function L(
J. Kleffe (1979)
Applicationes Mathematicae
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