fastmve {RobStatTM} | R Documentation |
Minimum Volume Ellipsoid covariance estimator
Description
This function uses a fast algorithm to compute the Minimum Volume Ellipsoid (MVE) for multivariate location and scatter.
Usage
fastmve(x, nsamp = 500)
Arguments
x |
data matrix (n x p) with cases stored in rows. |
nsamp |
number of random starts for the iterative algorithm, these are constructed using subsamples of the data. |
Details
This function computes the Minimum Volume
Ellipsoid (MVE) for multivariate location and scatter, using a
fast algorithm related to the fast algorithm for S-regression
estimators (see lmrob
).
Value
A list with the following components:
center |
a vector with the robust multivariate location estimate |
cov |
a matrix with the robust covariance / scatter matrix estimate |
scale |
A scalar that equals the median of the mahalanobis distances of the
data to the |
best |
Indices of the observations that correspond to the MVE estimator |
nsamp |
Number of random starts used for the iterative algorithm |
nsing |
Number of random subsamples (among the |
Author(s)
Matias Salibian-Barrera, matias@stat.ubc.ca
References
http://www.wiley.com/go/maronna/robust
Examples
data(bus)
X0 <- as.matrix(bus)
X1 <- X0[,-9]
tmp <- fastmve(X1)
round(tmp$cov[1:10, 1:10], 3)
tmp$center