cov.trob {MASS}R Documentation

Covariance Estimation for Multivariate t Distribution

Description

Estimates a covariance or correlation matrix assuming the data came from a multivariate t distribution: this provides some degree of robustness to outlier without giving a high breakdown point.

Usage

cov.trob(x, wt = rep(1, n), cor = FALSE, center = TRUE, nu = 5,
         maxit = 25, tol = 0.01)

Arguments

x data matrix. Missing values (NAs) are not allowed.
wt A vector of weights for each case: these are treated as if the case i actually occurred wt[i] times.
cor Flag to choose between returning the correlation (cor = TRUE) or covariance (cor = FALSE) matrix.
center a logical value or a numeric vector providing the location about which the covariance is to be taken. If center = FALSE, no centering is done; if center = TRUE the MLE of the location vector is used.
nu “degrees of freedom” for the multivariate t distribution. Must exceed 2 (so that the covariance matrix is finite).
maxit Maximum number of iterations in fitting.
tol Convergence tolerance for fitting.

Value

A list with the following components

cov the fitted covariance matrix.
center the estimated or specified location vector.
wt the specified weights: only returned if the wt argument was given.
n.obs the number of cases used in the fitting.
cor the fitted correlation matrix: only returned if cor = TRUE.
call The matched call.
iter The number of iterations used.

References

J. T. Kent, D. E. Tyler and Y. Vardi (1994) A curious likelihood identity for the multivariate t-distribution. Communications in Statistics—Simulation and Computation 23, 441–453.

Venables, W. N. and Ripley, B. D. (1999) Modern Applied Statistics with S-PLUS. Third Edition. Springer.

See Also

cov, cov.wt, cov.mve

Examples

data(stackloss)
cov.trob(stackloss)

[Package MASS version 7.2-33 Index]