• KernSmooth

  • Referenced in 911 articles [sw04586]
  • Kernel smoothing refers to a general methodology for recovery of the underlying structure in data ... required for a comprehensive understanding of kernel smoothing, and hence smoothing problems in general ... describe the principles, applications and analysis of kernel smoothers the authors concentrate on the simplest ... research in the field of kernel smoothing. But the bibliographical notes...
  • spatstat

  • Referenced in 129 articles [sw04429]
  • statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated...
  • ks

  • Referenced in 37 articles [sw08013]
  • package ks Kernel Smoothing: Kernel smoothers for univariate and multivariate data, including density functions, density...
  • SSVM

  • Referenced in 60 articles [sw12678]
  • using a completely arbitrary kernel. We term such reformulation a Smooth Support Vector Machine (SSVM ... light [T. Joachims, in: Advances in kernel methods – support vector learning, MIT Press: Cambridge...
  • sm

  • Referenced in 68 articles [sw12256]
  • book ’Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations’ Oxford...
  • LASSO

  • Referenced in 32 articles [sw02850]
  • various models such as wavelets, kernel machines, smoothing splines, multiclass logistic models...
  • Algorithm 876

  • Referenced in 11 articles [sw12906]
  • accuracy. The kernel function K(s,t) is to be moderately smooth ... interval is finite, Fie provides for kernel functions that behave in a variety of ways ... diagonal, viz. K(s,t) may be smooth, have a discontinuity in a low-order ... class of integral equations with moderately smooth kernel function...
  • kdecopula

  • Referenced in 6 articles [sw20374]
  • package kdecopula: Kernel Smoothing for Bivariate Copula Densities. Provides fast implementations of kernel smoothing techniques...
  • DBKGrad

  • Referenced in 5 articles [sw14541]
  • Adaptive Discrete Beta Kernel Techniques. Kernel smoothing represents a useful approach in the graduation ... there exist several options for performing kernel smoothing in statistical software packages, there have been ... variable or adaptive smoothing parameter, based on the further information provided by the exposed ... package DBKGrad is introduced. Among the available kernel approaches, it considers a recent discrete beta...
  • lokern

  • Referenced in 5 articles [sw14666]
  • Package. lokern: Kernel Regression Smoothing with Local or Global Plug-in Bandwidth. Kernel regression smoothing...
  • GoFKernel

  • Referenced in 4 articles [sw32640]
  • goodness-of-fit based on a kernel smoothing of the data...
  • sparr

  • Referenced in 4 articles [sw22046]
  • Relative Risk. Provides functions to estimate kernel-smoothed spatial and spatio-temporal densities and relative...
  • KernSmoothIRT

  • Referenced in 4 articles [sw16977]
  • item and option characteristic curves using kernel smoothing. It allows for optimal selection...
  • parallelMCMCcombine

  • Referenced in 3 articles [sw21115]
  • weighted averaging across subsets samples, and kernel smoothing across subset samples. The four functions assume...
  • sm

  • Referenced in 1 article [sw26319]
  • Nonparametric Kernel Smoothing Methods. The sm library in Xlisp-Stat. In this paper we describe ... library, a software for applying nonparametric kernel smoothing methods. The original version ... documented in their book Applied Smoothing Techniques for Data Analysis (1997). This is also ... methods implemented. The sm library provides kernel smoothing methods for obtaining nonparametric estimates of density...
  • ClusterKDE

  • Referenced in 1 article [sw36221]
  • algorithm for clustering based on univariate kernel density estimation, named ClusterKDE. It consists ... cluster is obtained by minimizing a smooth kernel function. Although in our applications we have ... used the univariate Gaussian kernel, any smooth kernel function can be used. The proposed algorithm...
  • decon

  • Referenced in 17 articles [sw11088]
  • deconvolution kernel estimation. Several methods for the selection of the data-driven smoothing parameter...
  • ChebCoInt

  • Referenced in 4 articles [sw32042]
  • nonlinear instances, with both smooth and nonsmooth kernels. We describe a Matlab toolbox which implements...
  • npbr

  • Referenced in 1 article [sw15636]
  • selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both ... local linear fitting, extreme values and kernel smoothing. The package also seamlessly allows for Monte...