robust (version 0.3-4)

fastcov: Orthogonalised Pariwise Covariance Estimation

Description

Compute a robust estimate of location and scatter using an orthogonalized pairwise estimator.

Usage

fastcov(x, control)

Arguments

x

a numeric matrix containing the data.

control

a list of control parameters. The utility function covRob.control creates a list of the control parameters and their default values. See details for the required control parameters and their default values.

Value

• a list with the following components:
• cov
  a numeric matrix containing the Stahel-Donoho estimate of the covariance/correlation matrix.
• center
  a numeric vector containing the Stahel-Donoho estimate of the location vector.
• raw.cov
  a numeric matrix containing the initial robust estimate of the covariance/correlation matrix.
• raw.center
  a numeric vector containing the initial robust estimate of the location vector.

References

Alqallaf, F. A. (2003). A new contamination model for robust estimation with large high-dimensional datasets. Ph.D. Thesis. http://hajek.stat.ubc.ca/~ruben/website/Fatemah_thesis.pdf

Maronna, R. A. and Zamar, R. H. (2002). Robust estimates of location and dispersion for high-dimensional datasets. Technometrics, 44, 307-317.

Details

This function is called by the high-level function covRob when either the pairwiseGK or the pairwiseQC estimator is specified (via the optional arguments estim = "pairwisegk" or estim = "pairwiseqc"). It may also be of interest to power users who want to compute a pairwise estimate with a minimum of fuss.

Presently the only control parameter is the name of the pairwise estimator, either "pairwisegk" or "pairwiseqc".

See Also

covRob, covRob.control.

Examples

data(woodmod.dat)
  X <- as.matrix(woodmod.dat)
  qc.control <- covRob.control("pairwiseqc")
  fastcov(X, qc.control)

  gk.control <- covRob.control("pairwisegk")
  fastcov(X, gk.control)