RobStatTM (version 1.0.2)

fastmve: 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.

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 center, multiplied by the determinant of the covariance matrix to the power 1/p

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 nsamp attempted) that failed (resulting in singular initial values)

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).

References

http://www.wiley.com/go/maronna/robust

Examples

# NOT RUN {
data(bus)
X0 <- as.matrix(bus)
X1 <- X0[,-9]
tmp <- fastmve(X1)
round(tmp$cov[1:10, 1:10], 3)
tmp$center

# }

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