wle.weights {wle}R Documentation

Weights based on Weighted Likelihood for the normal model

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


[Package wle version 0.9-3 Index]