wle.weights: 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.