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38 818 (0,189s)

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Kernel choice in bivariate kernel density derivative estimates

Kernel estimates belong to the most popular nonparametric method of estimating density and its derivatives. It is a known fact that these estimates depend on a bandwidth, which controls the smoothness of the es...

BB - Aplikovaná statistika, operační výzkum

  • 2011
  • D
  • Link
Result

Kernel choosing with respect to the bandwidth in kernel density estimates

Kernel density estimates belong to the most popular nonparametric density estimates. It is a known fact, that these estimates depend on a bandwidth, which controls the smoothness of the estimate, and on a ...

BB - Aplikovaná statistika, operační výzkum

  • 2010
  • O
Result

Convolutions of polynomial kernels

Kernel estimates are an integral part of non-parametric statistics. Convolutions of the kernels can be found in some expressions describing properties of kernel estimates. This paper presents the exact con...

BB - Aplikovaná statistika, operační výzkum

  • 2016
  • Jx
  • Link
Result

Kernel estimates of a derivative of a regession function

The paper is dealing with the criterion for the simultanous choosing of the parameters of kernel estimates of a derivative of a regression function....

BB - Aplikovaná statistika, operační výzkum

  • 2001
  • D
Result

An Improved Estimator for Removing Boundary Bias in Kernel Cumulative Distribution Function Estimation

In this paper we focus on kernel estimates of cumulative distribution functions that kernel distribution estimators are not consistent when estimating a~distribution in kernel ROC curve estima...

BA - Obecná matematika

  • 2008
  • D
Result

A generalized reflection method for kernel distribution and hazard functions estimation

In this paper we focus on kernel estimates of cumulative distribution. It is well known that kernel distribution estimators are not consistent when estimating, for example in kernel ROC curve ...

BA - Obecná matematika

  • 2011
  • Jx
Result

Iterative Method for Bandwidth Selection in Kernel Discriminant Analysis

Kernel estimates belong to very effective nonparametric estimates to the classical parametric approach in emipirical studies. Kernel estimates depend on a bandwidth matrix that controls smoothness of the <...

BB - Aplikovaná statistika, operační výzkum

  • 2014
  • D
  • Link
Result

Kernel Density Gradient Estimate

The aim of this contribution is to develop a method for a bandwidth matrix choice for kernel estimate of the first partial derivatives of the unknown density....

BB - Aplikovaná statistika, operační výzkum

  • 2011
  • D
  • Link
Result

Encyclopedia of Environmetrics : Kernel Density Estimation

Statistical properies of kernel estimates of densities are treated of. The attention is paid to the choice of smothing parametr which controls the smoothness of the estimate....

BB - Aplikovaná statistika, operační výzkum

  • 2012
  • C
  • Link
Result

Kernel Bivariate Density Toolbox

The toolbox for the kernel estimation of bivariate density in MATLAB (Kernel Bivariate Density Toolbox) was created. This toolbox contains many matlab scripts useful for kernel estimating of bivariate dens...

BA - Obecná matematika

  • 2011
  • R
  • Link
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