• KernSmooth

  • Referenced in 1018 articles [sw04586]
  • kernel smoothers the authors concentrate on the simplest nonparametric curve estimation setting, namely density ... amount of research in the field of kernel smoothing. But the bibliographical notes...
  • WAFO

  • Referenced in 25 articles [sw07370]
  • Fatigue life prediction for random loads; Theoretical density of rainflow cycles Sea modelling: Simulation ... period distributions Statistics: Extreme value analysis; Kernel density estimation, Hidden markov models...
  • GetDist

  • Referenced in 23 articles [sw29994]
  • LaTeX labels and prior bounds; Optimized Kernel Density Estimation - automated optimal bandwidth choice...
  • AS 176

  • Referenced in 17 articles [sw27946]
  • Algorithm AS 176. Kernel density estimation using the fast Fourier transform...
  • DENCLUE

  • Referenced in 12 articles [sw28734]
  • DENCLUE 2.0: Fast Clustering Based on Kernel Density Estimation. The Denclue algorithm employs a cluster ... model based on kernel density estimation. A cluster is defined by a local maximum ... estimated density function. Data points are assigned to clusters by hill climbing, i.e. points going ... hill climbing procedure for Gaussian kernels, which adjusts the step size automatically at no extra...
  • pdfCluster

  • Referenced in 22 articles [sw14640]
  • performs cluster analysis via nonparametric density estimation. Operationally, the kernel method is used throughout ... estimate the probability density function obtained by the kernel method, given a set of data...
  • evmix

  • Referenced in 8 articles [sw19523]
  • Modelling, Threshold Estimation and Boundary Corrected Kernel Density Estimation. The usual distribution functions, maximum likelihood ... extreme value mixture models are provided. Kernel density estimation including various boundary corrected kernel density...
  • ks

  • Referenced in 50 articles [sw08013]
  • Kernel Smoothing: Kernel smoothers for univariate and multivariate data, including density functions, density derivatives, cumulative...
  • sm

  • Referenced in 71 articles [sw12256]
  • Smoothing methods for nonparametric regression and density estimation. This is software linked to the book ... Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations’ Oxford University...
  • KDE Toolbox

  • Referenced in 7 articles [sw20503]
  • Kernel Density Estimation Toolbox for MATLAB. The KDE class is a general matlab class ... dimensional kernel density estimation. It is written in a mix of matlab ”.m” files...
  • MCMC

  • Referenced in 8 articles [sw03488]
  • plots, 2 dimensional clouds of points, kernel densities, and histograms. Calculate densities, cumulative distributions, quantiles...
  • akdensity

  • Referenced in 6 articles [sw37365]
  • Adaptive kernel density estimation. This insert describes the module akdensity. akdensity extends the official kdensity ... that estimates density functions by the kernel method. The extensions are of two types: akdensity ... allows the use of an “adaptive kernel” approach with varying, rather than fixed, bandwidths ... estimates pointwise variability bands around the estimated density functions...
  • SCWRL4

  • Referenced in 7 articles [sw22393]
  • backbone-dependent rotamer library based on kernel density estimates; 2) averaging over samples of conformations...
  • kdecopula

  • Referenced in 9 articles [sw20374]
  • package kdecopula: Kernel Smoothing for Bivariate Copula Densities. Provides fast implementations of kernel smoothing techniques...
  • GoFKernel

  • Referenced in 6 articles [sw32640]
  • Testing Goodness-of-Fit with the Kernel Density Estimator. Tests of goodness-of-fit based...
  • PointConv

  • Referenced in 5 articles [sw41516]
  • build deep convolutional networks. We treat convolution kernels as nonlinear functions of the local coordinates ... points comprised of weight and density functions. With respect to a given point, the weight ... perceptron networks and density functions through kernel density estimation. The most important contribution of this ... significantly improve its performance. The learned convolution kernel can be used to compute translation-invariant...
  • feature

  • Referenced in 4 articles [sw23520]
  • Local Inferential Feature Significance for Multivariate Kernel Density Estimation. Local inferential feature significance for multivariate ... kernel density estimation...
  • ClusterKDE

  • Referenced in 4 articles [sw36221]
  • algorithm for clustering based on kernel density estimation. In this paper, we present an algorithm ... clustering based on univariate kernel density estimation, named ClusterKDE. It consists of an iterative procedure ... cluster is obtained by minimizing a smooth kernel function. Although in our applications we have...
  • lsbs

  • Referenced in 6 articles [sw28186]
  • Estimation. Bandwidth selection for kernel density estimators of 2-d level sets and highest density...
  • nprobust

  • Referenced in 3 articles [sw30833]
  • Methods using Local Polynomial Regression and Kernel Density Estimation. Tools for data-driven statistical analysis ... using local polynomial regression and kernel density estimation methods as described in Calonico, Cattaneo ... local polynomial bandwidth selection, kdrobust() for kernel density point estimation and robust bias-corrected inference ... kdbwselect() for kernel density bandwidth selection, and nprobust.plot() for plotting results. The main methodological...