Package: pendensity 0.2.13

pendensity: Density Estimation with a Penalized Mixture Approach

Estimation of univariate (conditional) densities using penalized B-splines with automatic selection of optimal smoothing parameter.

Authors:Christian Schellhase

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pendensity.pdf |pendensity.html✨
pendensity/json (API)

# Install 'pendensity' in R:

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

Datasets:

Allianz - Daily final prices (DAX) of the German stock Allianz in the years 2006 and 2007
DeutscheBank - Daily final prices (DAX) of the German stock Deutsche Bank in the years 2006 and 2007

On CRAN:

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

2.00 score 2 scripts 313 downloads 6 exports 48 dependencies

Last updated 6 years agofrom:540fff4ac7. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 25 2024
R-4.5-win	NOTE	Oct 25 2024
R-4.5-linux	NOTE	Oct 25 2024
R-4.4-win	NOTE	Oct 25 2024
R-4.4-mac	NOTE	Oct 25 2024
R-4.3-win	NOTE	Oct 25 2024
R-4.3-mac	NOTE	Oct 25 2024

Exports:dpendensity pendensity plot.pendensity ppendensity print.pendensity test.equal

Dependencies:ash bitops cli cluster colorspace deSolve fansi farver fda fds FNN ggplot2 glue gtable hdrcde isoband kernlab KernSmooth ks labeling lattice lifecycle locfit magrittr MASS Matrix mclust mgcv multicool munsell mvtnorm nlme pcaPP pillar pkgconfig pracma R6 rainbow RColorBrewer Rcpp RCurl rlang scales tibble utf8 vctrs viridisLite withr

pendensity

Rendered frompendensity.Rnwusingutils::Sweaveon Oct 25 2024.

Last update: 2019-04-07
Started: 2014-01-21

Citation

Readme and manuals

Help Manual

Help page	Topics
The package 'pendensity' offers routines for estimating penalized unconditional and conditional (on factor groups) densities.	pendensity-package
Daily final prices (DAX) of the German stock Allianz in the years 2006 and 2007	Allianz
Calculating the bias of the parameter beta	bias.par
Calculating the actual weights ck	ck
Calculating the penalty matrix	D.m
Calculating the first derivative of the pendensity likelihood function w.r.t. parameter beta	Derv1
Calculating the second order derivative with and without penalty	Derv2
Daily final prices (DAX) of the German stock Deutsche Bank in the years 2006 and 2007	DeutscheBank
These functions are used for calculating the empirical and theoretical distribution functions.	cal.int distr.func distr.func.help poly.part
Calculating the fitted density or distribution	dpendensity ppendensity
Calculating the actual fitted values 'f.hat' of the estimated density function f for the response y	f.hat
Calculates the difference matrix of order m	L.mat
Calculating the marginal likelihood	marg.likelihood
Calculating the AIC value	my.AIC
my.bspline	my.bspline
my.positive.definite.solve	my.positive.definite.solve
Calculating the new parameter beta	new.beta.val
Calculating new penalty parameter lambda	new.lambda
Calculating the log likelihood	pen.log.like
Formula interpretation and data transfer	pendenForm string.help
Calculating penalized density	pendensity
Plotting estimated penalized densities	plot plot.pendensity
Printing the main results of the (conditional) penalized density estimation	print print.pendensity
Testing pairwise equality of densities	test.equal
Calculating the variance of the parameters	variance.par
Calculating variance and standard deviance of each observation.	variance.val