Package: kedd 1.0.4

Iago Giné-Vázquez

kedd: Kernel Estimator and Bandwidth Selection for Density and Its Derivatives

Smoothing techniques and computing bandwidth selectors of the nth derivative of a probability density for one-dimensional data (described in Arsalane Chouaib Guidoum (2020) <arxiv:2012.06102> [stat.CO]).

Authors:Iago Giné-Vázquez [cre], Arsalane Chouaib Guidoum [aut]

kedd_1.0.4.tar.gz
kedd_1.0.4.zip(r-4.7-any)kedd_1.0.4.zip(r-4.6-any)kedd_1.0.4.zip(r-4.5-any)
kedd_1.0.4.tgz(r-4.6-any)kedd_1.0.4.tgz(r-4.5-any)
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kedd_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
kedd/json (API)

# Install 'kedd' in R:
install.packages('kedd', repos = c('https://iagogv3.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://gitlab.com/iagogv/kedd

Datasets:

On CRAN:

Conda:

6.32 score 2 packages 351 scripts 484 downloads 1 mentions 46 exports 0 dependencies

Last updated from:6542913245. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK116
source / vignettesOK222
linux-releaseOK94
macos-releaseOK94
macos-oldrelOK104
windows-develOK82
windows-releaseOK64
windows-oldrelOK73
wasm-releaseOK80

Exports:dkdedkde.defaulth.amiseh.amise.defaulth.bcvh.bcv.defaulth.ccvh.ccv.defaulth.mcvh.mcv.defaulth.mlcvh.mlcv.defaulth.tcvh.tcv.defaulth.ucvh.ucv.defaultkernel.convkernel.conv.defaultkernel.funkernel.fun.defaultlines.dkdelines.h.amiselines.h.bcvlines.h.ccvlines.h.mcvlines.h.mlcvlines.h.tcvlines.h.ucvplot.dkdeplot.h.amiseplot.h.bcvplot.h.ccvplot.h.mcvplot.h.mlcvplot.h.tcvplot.h.ucvplot.kernel.convplot.kernel.funprint.dkdeprint.h.amiseprint.h.bcvprint.h.ccvprint.h.mcvprint.h.mlcvprint.h.tcvprint.h.ucv

Dependencies:

Introduction to kedd
Introduction | Documentation | Requirements | Licence | Collaboration and citation
Rendered fromintro.Rnwusingutils::Sweave

Last update: 2024-01-26
Started: 2013-08-14

Kernel estimator and bandwidth selection for density and its derivatives
Introduction | Convolutions and derivatives in kernels | Kernel density derivative estimator | Bandwidth selections | Summary
Rendered fromkedd.Rnwusingutils::Sweave

Last update: 2024-01-26
Started: 2013-08-14

Readme and manuals

Help Manual

Help pageTopics
Kernel Estimator and Bandwidth Selection for Density and Its Derivativeskedd-package kedd
Datasetsbimodal claw kurtotic outlier trimodal
Derivatives of Kernel Density Estimatordkde dkde.default print.dkde
AMISE for Optimal Bandwidth Selectorsh.amise h.amise.default print.h.amise
Biased Cross-Validation for Bandwidth Selectionh.bcv h.bcv.default print.h.bcv
Complete Cross-Validation for Bandwidth Selectionh.ccv h.ccv.default print.h.ccv
Modified Cross-Validation for Bandwidth Selectionh.mcv h.mcv.default print.h.mcv
Maximum-Likelihood Cross-validation for Bandwidth Selectionh.mlcv h.mlcv.default print.h.mlcv
Trimmed Cross-Validation for Bandwidth Selectionh.tcv h.tcv.default print.h.tcv
Unbiased (Least-Squares) Cross-Validation for Bandwidth Selectionh.ucv h.ucv.default print.h.ucv
Convolutions of r'th Derivative for Kernel Functionkernel.conv kernel.conv.default
Derivatives of Kernel Functionkernel.fun kernel.fun.default
Plot for Kernel Density Derivative Estimatelines.dkde plot.dkde
Plot for Asymptotic Mean Integrated Squared Errorlines.h.amise plot.h.amise
Plot for Biased Cross-Validationlines.h.bcv plot.h.bcv
Plot for Complete Cross-Validationlines.h.ccv plot.h.ccv
Plot for Modified Cross-Validationlines.h.mcv plot.h.mcv
Plot for Maximum-Likelihood Cross-validationlines.h.mlcv plot.h.mlcv
Plot for Trimmed Cross-Validationlines.h.tcv plot.h.tcv
Plot for Unbiased Cross-Validationlines.h.ucv plot.h.ucv
Plot for Convolutions of r'th Derivative Kernel Functionplot.kernel.conv
Plot of r'th Derivative Kernel Functionplot.kernel.fun