Displaying similar documents to “Minimax Estimators and ...-Minimax Estimators for a Bounded Normal Mean Under the Loss ip(0, d) =I0-dIp”

Kernel estimators and the Dvoretzky-Kiefer-Wolfowitz inequality

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.

Bayesian like R- and M- estimators of change points

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.

An empirical evaluation of small area estimators.

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...