wle.weights: Weights based on Weighted Likelihood for the normal model

In wle: Weighted Likelihood Estimation

Description

This function evaluated the weights for the vector 'x' using the vector 'y' in the estimation of the density by the kernel density estimator.

Usage

wle.weights(x, y=NULL, smooth=0.0031, sigma2, raf=1,
  location=FALSE, max.iter=1000, tol=10^(-6))

Arguments

x	the data set for which the weights would be calculate.
y	the data set used to calculate the weights.
smooth	the value of the smoothing parameter.
sigma2	an estimate of the variance.
raf	type of Residual adjustment function to be use: raf="HD": Hellinger Distance RAF, raf="NED": Negative Exponential Disparity RAF, raf="SCHI2": Symmetric Chi-Squared Disparity RAF.
location	if TRUE the location is estimated. Only available when y=NULL.
max.iter	maximum number of iterations.
tol	the absolute accuracy to be used to achieve convergence of the algorithm.

Value

weights	the weights associated to the x vector.
location	the location.
conv	TRUE if the convergence is achived.

Author(s)

Claudio Agostinelli

wle documentation built on May 29, 2017, 11:48 a.m.