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. (2002) Modern Applied Statistics with S-PLUS. Fourth Edition. Springer.

cov, cov.wt, cov.mve
cov.trob(stackloss)