Calculating the variance and standard deviance of each observation. Therefore we use the variance of the parameter set beta, called 'var.par'.
variance.val(base.den, var.par, weight, K, x, list.len, Z, x.factor, y.val=NULL)
base values
variance of the parameter set beta
weights ck
number of knots
covariates
number of covariate combinations
covariate matrix
list of covariate combinations
optimal values for calculating the variance in any point yi in the case of a factorial density
Returning a vector with the standard deviance of each observation.
Density Estimation with a Penalized Mixture Approach, Schellhase C. and Kauermann G. (2012), Computational Statistics 27 (4), p. 757-777.