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Optimum kernels.

Kernel smoothers belong to the most popular nonparametric functional estimates. They provide a simple way of finding structure in data. Kernel smoothing can be very well applied on the regression model. In the context of kernel<...

BB - Aplikovaná statistika, operační výzkum

  • 2004
  • Jx
Result

Remarks to optimum kernels and boundary optimum kernels

Kernel smoothers belong to the most popular nonparametric functional estimates used for describing data structure. They can be applied on the fix design of kernel estimatesof a regression function, the choice of a kernel ca...

BB - Aplikovaná statistika, operační výzkum

  • 2008
  • Jx
Result

Kernel Ridge Regression with Odd Kernels in Financial Time Series Prediction

A new type of kernels called odd kernels is proposed to model dependencies by odd functions. Odd kernels could be simply constructed from the most of traditional kernels. Although usability of odd kernels ...

JC - Počítačový hardware a software

  • 2011
  • D
Result

Kernel choice with respect to the bandwidth in kernel density estimates

We focus on the kernel function choice, especially on kernels with a bounded support. Our aim is to study the optimality of the kernel with respect to the bandwidth choice. A simulation study brings comparison of the ke...

BB - Aplikovaná statistika, operační výzkum

  • 2011
  • D
Result

Kernel choosing with respect to the bandwidth in kernel density estimates

Kernel density estimates belong to the most popular nonparametric density controls the smoothness of the estimate, and on a kernel, which plays a role. in Duong & Hazelton (2005), Sain et al. (1994). We focus on the kernel

BB - Aplikovaná statistika, operační výzkum

  • 2010
  • O
Result

Kernel choice in bivariate kernel density derivative estimates

Kernel estimates belong to the most popular nonparametric method of estimating on a bandwidth, which controls the smoothness of the estimate, and on a kernel, which plays a roleof a weighting function. We focus on a kernel ...

BB - Aplikovaná statistika, operační výzkum

  • 2011
  • D
  • Link
Result

Kernel Ridge Regression with Odd Kernels in Financial Time Series Prediction

Kernel ridge regression is applied to the prediction of short-time trends of kernels is proposed to model dependencies by odd functions. Experimental results for both traditional kernels and their odd counterparts are repor...

JC - Počítačový hardware a software

  • 2011
  • 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 construction of convo...

BB - Aplikovaná statistika, operační výzkum

  • 2016
  • Jx
  • Link
Result

Some Remarks on Kernels

The aim of this paper is to present constructions of minimum variance kernels and smooth kernels by means of the Legendre polynomials and the Gegenbauer polynomials as well....

BA - Obecná matematika

  • 2000
  • Jx
Result

Kernel Convolutions and their Application

Convolutions can be found in some expressions used in kernel estimates. Knowing the exact shape of the kernel convolutions is useful for faster evaluation of such expressions. This paper presents the exact construction of convolutio...

BB - Aplikovaná statistika, operační výzkum

  • 2011
  • O
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