cov.trob                package: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)

