pendensity-package: The package 'pendensity' offers routines for estimating...
In pendensity: Density Estimation with a Penalized Mixture Approach

Description Details Author(s) References Examples

The package 'pendensity' offers routines for estimating penalized unconditional and conditional (on factor groups) densities. For details see the description of the function pendensity.

Package:	pendensity
Type:	Package
Version:	0.2.12
Date:	2019-04-07
License: GPL (>= 2) LazyLoad:	yes

The packages contributes the function 'pendensity()' for estimating densities using penalized splines techniques.

Christian Schellhase <christian.schellhase@gmx.net>

Density Estimation with a Penalized Mixture Approach, Schellhase C. and Kauermann G. (2012), Computational Statistics 27 (4), p. 757-777.

y <- rnorm(100)
test <- pendensity(y~1)
plot(test)

#################

#second simple example
#with covariate

x <- rep(c(0,1),200)
y <- rnorm(400,x*0.2,1)
test <- pendensity(y~as.factor(x),lambda0=2e+07)
plot(test)

#################

#calculate the value at some (maybe not observed) value yi=c(0,1) of the estimated density

plot(test,val=c(0,1))

#################

#density-example of the stock exchange Allianz in 2006

data(Allianz)
time.Allianz <- strptime(Allianz[,1],form="%d.%m.%y")

#looking for all dates in 2006
data.Allianz <- Allianz[which(time.Allianz$year==106),2]

#building differences of first order
d.Allianz <- diff(data.Allianz)

#estimating the density, choosing a special start value for lambda
density.Allianz <- pendensity(d.Allianz~1,lambda0=90000)
plot(density.Allianz)