KurtSDNew: Robust multivariate location and scatter estimators

In msalibian/RobStatTM: Robust Statistics: Theory and Methods

Robust multivariate location and scatter estimators

Description

This function computes robust multivariate location and scatter estimators using both random and deterministic starting points.

Usage

initPP(X, muldirand = 20, muldifix = 10, dirmin = 1000)

Arguments

X	a data matrix with observations in rows.
muldirand	used to determine the number of random directions (candidates), which is max(p*muldirand, dirmin), where p is the number of columns in X.
muldifix	used to determine the number of random directions (candidates), which is min(n, 2*muldifix*p).
dirmin	minimum number of random directions

Details

This function computes robust multivariate location and scatter using both Pen~a-Prieto and random candidates.

Value

A list with the following components:

idx	A zero/one vector with ones in the positions of the suspected outliers
disma	Robust squared Mahalanobis distances
center	Robust mean estimate
cova	Robust covariance matrix estimate
t	Outlyingness of data points

Author(s)

Ricardo Maronna, [e-mail], based on original code by D. Pen~a and J. Prieto

References

http://www.wiley.com/go/maronna/robust

Examples

data(bus)
X0 <- as.matrix(bus)
X1 <- X0[,-9]
tmp <- initPP(X1)
round(tmp$cov[1:10, 1:10], 3)
tmp$center

msalibian/RobStatTM documentation built on April 24, 2024, 5:10 a.m.