Robust Covariance Matrix

DESCRIPTION:

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

USAGE:

cov.lmRob(x) 

REQUIRED ARGUMENTS:

x
an object of class "lmRob".

VALUE:

a matrix of robust covariances of the coefficient estimates.

REFERENCES:

Gervini, D., and Yohai, V. J. (1999). A class of robust and fully efficient regression estimates, mimeo, Universidad de Buenos Aires.

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.

Maronna, R. A., and Yohai, V. J. (1999). Robust regression with both continuous and categorical predictors, mimeo, Universidad de Buenos Aires.

SEE ALSO:

, .

EXAMPLES:

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