cov.trob | R Documentation |
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.
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
cov |
the fitted covariance matrix. |
center |
the estimated or specified location vector. |
wt |
the specified weights: only returned if the |
n.obs |
the number of cases used in the fitting. |
cor |
the fitted correlation matrix: only returned if |
call |
The matched call. |
iter |
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. (2002) Modern Applied Statistics with S-PLUS. Fourth Edition. Springer.
cov
, cov.wt
, cov.mve
cov.trob(stackloss)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.