Robust Covariance Matrix

DESCRIPTION:

Returns a robust covariance matrix of the coefficient estimates in a linear model, as estimated by lmRobMM function.

USAGE:

cov.lmRobMM(x) 

REQUIRED ARGUMENTS:

x
an object of class "lmRobMM".

VALUE:

a matrix of robust covariances of the coefficient estimates.

DETAILS:

If the coefficient estimates are the initial S-estimates, the covariance matrix of the initial S-estimates is returned; if the coefficient estimates are the final M-estimates, the covariance matrix of the final M-estimates is returned.

REFERENCES:

Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., and Stahel, W. A. (1986). Robust statistics: the approach based on influence functions. John & Wiley.

Huber, P. J. (1981). Robust statistics. John & Wiley.

Marazzi, A. (1993). Algorithms, routines, and S functions for robust statistics. Wadsworth & Brooks/Cole, Pacific Grove, CA.

SEE ALSO:

, .

EXAMPLES:

stack.df <- data.frame(Loss=stack.loss,stack.x) 
stack.robust <- lmRobMM(Loss~Air.Flow+Water.Temp+Acid.Conc.,data=stack.df) 
stack.cov <- cov.lmRobMM(stack.robust)