Sboot_loccov {FRB}R Documentation

Fast and Robust Bootstrap for S-estimates of location/covariance

Description

Calculates bootstrapped S-estimates using the Fast and Robust Bootstrap method.

Usage

Sboot_loccov(Y, R, ests = Sest_loccov(Y))

Arguments

Y matrix or data frame
R number of bootstrap samples
ests original S-estimates as returned by Sest_loccov()

Details

This function is called by FRBpcaS and FRBhotellingS, it is typically not to be used on its own. It requires the result of Sest_loccov applied on Y, supplied through the argument ests. If ests is not provided, Sest_loccov will be called with default arguments.

The fast and robust bootstrap was first developed by Salibian-Barrera and Zamar (2002) for univariate regression MM-estimators.

The value centered gives a matrix with R columns and p+p*p rows (p is the number of variables in Y), containing the recalculated estimates of the S-location and -covariance. Each column represents a different bootstrap sample. The first p rows are the location estimates and the next p*p rows are the covariance estimates (vectorized). The estimates are centered by the original estimates, which are also returned through Sest.

Value

A list containing:

centered recalculated estimates of location and covariance (centered by original estimates)
Sest original estimates of location and covariance

Author(s)

Gert Willems and Ella Roelant

References

See Also

FRBpcaS, FRBhotellingS, Sest_loccov, MMboot_loccov

Examples


Y <- matrix(rnorm(50*5), ncol=5)
Sests <- Sest_loccov(Y, bdp = 0.25) 
bootresult <- Sboot_loccov(Y, R = 1000, ests = Sests)


[Package FRB version 1.4 Index]