Density Estimation with a Penalized Mixture Approach

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Documentation for package ‘pendensity’ version 0.2

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