varrob: Robust variance

View source: R/acprob.R

VarRobR Documentation

Robust variance

Description

Compute a robust variance

Usage

varrob(x,h,D=NULL,kernel="gaussien")

Arguments

x

Matrix / data frame

h

Scalar: bandwidth of the Kernel

kernel

The kernel used. This must be one of '"gaussien"', '"quartic"', '"triweight"', '"epanechikov"' , '"cosinus"' or '"uniform"'

D

A product scalar matrix / une matrice de produit scalaire

Details

U compute robust variance. U_n^{-1} = S_n^{-1} - 1/h V_n^{-1}

S_n=\frac{\sum_{i=1}^{n}K(||X_i||_{V_n^{-1}}/h)(X_i-\mu_n)(X_i-\mu_n)'}{\sum_{i=1}^nK(||X_i||_{V_n^{-1}}/h)}

with \mu_n estimator of the mean.

K compute a kernel.

Value

A matrix

Author(s)

Antoine Lucas

References

H. Caussinus, S. Hakam, A. Ruiz-Gazen Projections revelatrices controlees: groupements et structures diverses. 2002, to appear in Rev. Statist. Appli.

See Also

acp princomp


amap documentation built on Oct. 30, 2024, 9:09 a.m.