Package: pencopulaCond 0.2

Christian Schellhase

pencopulaCond: Estimating Non-Simplified Vine Copulas Using Penalized Splines

Estimating Non-Simplified Vine Copulas Using Penalized Splines.

Authors:Christian Schellhase <[email protected]>

pencopulaCond_0.2.tar.gz
pencopulaCond_0.2.tar.gz(r-4.5-noble)pencopulaCond_0.2.tar.gz(r-4.4-noble)
pencopulaCond_0.2.tgz(r-4.4-emscripten)pencopulaCond_0.2.tgz(r-4.3-emscripten)
pencopulaCond.pdf |pencopulaCond.html✨
pencopulaCond/json (API)

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

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 1 scripts 169 downloads 8 exports 68 dependencies

Last updated 8 years agofrom:bf0aff34f4. Checks:1 OK, 1 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 18 2025
R-4.5-linuxNOTEFeb 18 2025

Exports:cal.Dvinecal.vinehierarch.bsmy.bsplinepencopulaplot.pencopulaprint.pencopulavine

Dependencies:ADGofTestashbitopscliclustercodetoolscolorspacecpp11deldirdeSolvedoParallelfansifarverfdafdsFNNforeachggplot2gluegridExtragtablehdrcdeigraphinterpisobanditeratorsjpegkernlabKernSmoothkslabelinglatticelatticeExtralifecyclelocfitmagrittrMASSMatrixmclustmgcvmulticoolmunsellmvtnormnlmenumDerivpacotestpcaPPpillarpkgconfigpngpracmaquadprogR6rainbowRColorBrewerRcppRcppArmadilloRcppEigenRCurlrlangscalestibbleTSPutf8vctrsVineCopulaviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Estimating Non-Simplified Vine Copulas Using Penalized SplinespencopulaCond-package
Estimating Non-Simplified Vine Copulas Using Penalized Splinescal.Dvine
Estimating Non-Simplified Vine Copulas Using Penalized Splinescal.vine
Calculating the first derivative of the pencopula likelihood function w.r.t. parameter bDerv1
Calculating the second order derivative with and without penalty.Derv2
These functions are used for calculating the integral of the B-spline density basis.distr.func.help poly.part
Calculating the actual fitted values 'f.hat.val' of the estimated density functionf.hat.val
Construction of the hierarchical B-spline density basis.hierarch.bs
Calculating the knots.knots.order knots.start knots.transform
Calculating the marginal likelihoodmarg.likelihood
my.bsplineint.my.bspline my.bspline
Calculating the AIC-valuemy.IC
Iterative loop for calculating the optimal coefficients 'b'.my.loop
my.positive.definite.solvemy.positive.definite.solve
Calculating new weights b.new.weights
Calculating the log likelihoodpen.log.like
Calculating the penalty matrix P(lambda)penalty.matrix
Calculating penalized (conditional) copula density with penalized hierarchical B-splinespencopula
Formula interpretation and data transferpendenForm
Plot the estimated copula density or copula distribution.plot.pencopula
Printing the main results of the penalized copula density estimationprint print.pencopula
"Estimating Non-Simplified Vine Copulas Using Penalized Splines"vine