Package: kdecopula 0.9.3

kdecopula: Kernel Smoothing for Bivariate Copula Densities

Provides fast implementations of kernel smoothing techniques for bivariate copula densities, in particular density estimation and resampling, see Nagler (2018) <doi:10.18637/jss.v084.i07>.

Authors:Thomas Nagler [aut, cre], Kuangyu Wen [ctb]

kdecopula_0.9.3.tar.gz
kdecopula_0.9.3.zip(r-4.7)kdecopula_0.9.3.zip(r-4.6)kdecopula_0.9.3.zip(r-4.5)
kdecopula_0.9.3.tgz(r-4.6-x86_64)kdecopula_0.9.3.tgz(r-4.6-arm64)kdecopula_0.9.3.tgz(r-4.5-x86_64)kdecopula_0.9.3.tgz(r-4.5-arm64)
kdecopula_0.9.3.tar.gz(r-4.7-arm64)kdecopula_0.9.3.tar.gz(r-4.7-x86_64)kdecopula_0.9.3.tar.gz(r-4.6-arm64)kdecopula_0.9.3.tar.gz(r-4.6-x86_64)
kdecopula_0.9.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
kdecopula/json (API)

# Install 'kdecopula' in R:

install.packages('kdecopula', repos = c('https://tnagler.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tnagler/kdecopula/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

wdbc - Wisconsin Diagnostic Breast Cancer

On CRAN:

openblas cpp

6.26 score 9 stars 1 packages 39 scripts 3.5k downloads 13 exports 6 dependencies

Last updated from:b625d814f1. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	193
linux-devel-x86_64	OK	211
source / vignettes	OK	205
linux-release-arm64	OK	216
linux-release-x86_64	OK	197
macos-release-arm64	OK	140
macos-release-x86_64	OK	251
macos-oldrel-arm64	OK	130
macos-oldrel-x86_64	OK	227
windows-devel	OK	174
windows-release	OK	163
windows-oldrel	OK	164
wasm-release	OK	167

Exports:bw_beta bw_mr bw_t bw_tll bw_tll_nn bw_tt_cv bw_tt_pi dep_measures dkdecop hkdecop kdecop pkdecop rkdecop

Dependencies:lattice locfit qrng quadprog Rcpp RcppArmadillo

kdecopula

Rendered fromkdecopula.pdf.asisusingR.rsp::asis

Last update: 2017-01-14
Started: 2016-01-20

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Bandwidth selection for the Bernstein copula estimator	bw_bern
Bandwidth selection for the beta kernel estimator	bw_beta
Bandwidth selection for the mirror-reflection estimator	bw_mr
Bandwidth selection for the transformation kernel estimator	bw_t
Bandwidth selection for the transformation local likelihood estimator	bw_tll
Nearest-neighbor bandwidth selection for the transformation local likelihood estimator	bw_tll_nn
Nearest-neighbor bandwidth selection for the tapered transformation estimator	bw_tt_cv bw_tt_pi
Dependence measures of a 'kdecop()' fit	dep_measures
Working with 'kdecopula' objects	dkdecop pkdecop rkdecop
Extract fitted values from a 'kdecop()' fits.	fitted.kdecopula
H-function and inverse of a 'kdecop()' fit	hkdecop
Bivariate kernel copula density estimation	kdecop
Kernel Smoothing for Bivariate Copula Densities	kdecopula-package kdecopula
Log-Likelihood of a 'kdecopula' object	logLik.kdecopula
Plotting 'kdecopula' objects	contour.kdecopula plot.kdecopula
Prediction method for 'kdecop()' fits	predict.kdecopula
Simulate data from a 'kdecop()' fit.	simulate.kdecopula
Wisconsin Diagnostic Breast Cancer (WDBC)	wdbc