| variance.par {pendensity} | R Documentation |
Calculating the variance of the parameters
Description
Calculating the variance of the parameters of the estimation, depending on the second order derivative and the penalized second order derivative of the density estimation.
Usage
variance.par(penden.env)
Arguments
penden.env |
Containing all information, environment of pendensity() |
Details
The variance of the parameters of the estimation results as the product of the inverse of the penalized second order derivative times the second order derivative without penalization time the inverse of the penalized second order derivative.
V(\beta, \lambda_0)=I_p^{-1}(\beta, \lambda) I_p(\beta, \lambda=0) I_p^{-1}(\beta, \lambda) with I_p(\beta^{-1}, \lambda)=E_{f(y)}\bigl\{J_p(\beta, \lambda)\bigr\}
The needed values are saved in the environment.
Value
The return is a variance matrix of the dimension (K-1)x(K-1).
Author(s)
Christian Schellhase <cschellhase@wiwi.uni-bielefeld.de>
References
Density Estimation with a Penalized Mixture Approach, Schellhase C. and Kauermann G. (2012), Computational Statistics 27 (4), p. 757-777.