Displaying similar documents to “Polynomial and spline estimators of the distribution function with prescribed accuracy”

Box-spline histograms for multivariate density estimation

Karol Dziedziul, Piotr Paluszek (2010)

Applicationes Mathematicae

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The uniform approach to calculation of MISE for histogram and density box-spline estimators gives us a possibility to obtain estimators of derivatives of densities and the asymptotic constant.

A maximum likelihood estimator of an inhomogeneous Poisson point processes intensity using beta splines

Pavel Krejčíř (2000)

Kybernetika

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The problem of estimating the intensity of a non-stationary Poisson point process arises in many applications. Besides non parametric solutions, e. g. kernel estimators, parametric methods based on maximum likelihood estimation are of interest. In the present paper we have developed an approach in which the parametric function is represented by two-dimensional beta-splines.

Nonparametric estimation of simplified vine copula models: comparison of methods

Thomas Nagler, Christian Schellhase, Claudia Czado (2017)

Dependence Modeling

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In the last decade, simplified vine copula models have been an active area of research. They build a high dimensional probability density from the product of marginals densities and bivariate copula densities. Besides parametric models, several approaches to nonparametric estimation of vine copulas have been proposed. In this article, we extend these approaches and compare them in an extensive simulation study and a real data application. We identify several factors driving the relative...

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.

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...

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.