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

 `1` ```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 <cschellhase@wiwi.uni-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.