cov.trob.RdEstimates 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.
cov.trob(x, wt = rep(1, n), cor = FALSE, center = TRUE, nu = 5, maxit = 25, tol = 0.01)
| x | data matrix. Missing values (NAs) are not allowed. |
|---|---|
| wt | A vector of weights for each case: these are treated as if the case |
| cor | Flag to choose between returning the correlation ( |
| center | a logical value or a numeric vector providing the location about which
the covariance is to be taken. If |
| 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. |
A list with the following components
the fitted covariance matrix.
the estimated or specified location vector.
the specified weights: only returned if the wt argument was given.
the number of cases used in the fitting.
the fitted correlation matrix: only returned if cor = TRUE.
The matched call.
The number of iterations used.
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.
cov.trob(stackloss)#> $cov #> Air.Flow Water.Temp Acid.Conc. stack.loss #> Air.Flow 60.47035 17.027203 18.554452 62.28032 #> Water.Temp 17.02720 8.085857 5.604132 20.50469 #> Acid.Conc. 18.55445 5.604132 24.404633 16.91085 #> stack.loss 62.28032 20.504687 16.910855 72.80743 #> #> $center #> Air.Flow Water.Temp Acid.Conc. stack.loss #> 58.96905 20.79263 86.05588 16.09028 #> #> $n.obs #> [1] 21 #> #> $call #> cov.trob(x = stackloss) #> #> $iter #> [1] 5 #>