variance.val: Calculating variance and standard deviance of each...

In pendensity: Density Estimation with a Penalized Mixture Approach

Description

Calculating the variance and standard deviance of each observation. Therefore we use the variance of the parameter set beta, called 'var.par'.

Usage

variance.val(base.den, var.par, weight, K, x, list.len, Z, x.factor, y.val=NULL)

Arguments

base.den	base values
var.par	variance of the parameter set beta
weight	weights ck
K	number of knots
x	covariates
list.len	number of covariate combinations
Z	covariate matrix
x.factor	list of covariate combinations
y.val	optimal values for calculating the variance in any point yi in the case of a factorial density

Value

Returning a vector with the standard deviance of each observation.

Author(s)

Christian Schellhase <[e-mail]-bielefeld>

References

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

pendensity documentation built on May 2, 2019, 3:58 a.m.