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]