OBRECovarianceMatrix {OBRE}

Function that computes the OBRE covariance matrix.

Description

The function computes matrices M (Jacobian) and Q (Variability) and uses them to evaluate the covariance matrix V.

Usage

OBRECovarianceMatrix(lOBRE)

Arguments

lOBRE

List of all the variables resulting from the OBRE computation.

Value

A list containing Jacobian of the estimate function, variability and asymptotic covariance matrices, as well as the relative efficiency with respect to Maximum Likelihood Estimator

References

Hampel, F., Ronchetti, E., Rousseeuw, P. & Stahel, W. (1985). Robust Statistics. The approach based on influence function. John Wiley and Sons Ltd., Chichester, UK.

Heritier S, Cantoni E, Copt S, Victoria-Feser M (2011). Robust Methods in Biostatistics. John Wiley and Sons Ltd., Chichester, UK.

Examples

try({distrForOBRE <- densityExpressions(strDistribution = "normal")
simData = c(rnorm(1000, 12, 2),200,150)
estOBRE <- OBRE(nvData = simData, strDistribution = distrForOBRE, nCParOBRE = 3)
lOBRECov = OBRECovarianceMatrix(estOBRE)})