Grocer Function

NAME

robust - robust regression

CALLING SEQUENCE

[rrobust]=robust(wfunc,wparm,grocer_namey, arg1,...,argn)

PARAMETERS

Input

Output

DESCRIPTION

Computes robust regression using iteratively reweighted least-squares. The first argument control the weighting scheme. The second argument controls the weighting parameter. Endogenous variable must be given third, as a vector, a ts, between quotes (if the user wants to keep the name of the variable in the tlist result and for the printings) or not. Exogenous variables are given after, in one of the formats authorized for the endogenous one, or in matrix format. The program displays on screen various results (coefficients, tstat, Rē, Durbin and Watson, first order autocorrelation of residuals,...) except if the user has entered the argument 'noprint' anywhere after the first argument.

EXAMPLE

1) r = robust('huber', 0.000338','del(lm1-lp)','del(lp)','del(lagts(1,lm1-lp-ly))','rnet', 'lagts(1,lm1-lp-ly)','cte')
2) r = robust('andrew', 0.000338','del(lm1-lp)','del(lp)','del(lagts(1,lm1-lp-ly))','rnet', 'lagts(1,lm1-lp-ly)','cte', 'noprint')

These examples shows the results of a robust regression on Hendry and Ericsson's preferred regression, using huber's weighting scheme in example 1 and andrew's one in example 2. Results are not displayed in example 2.

AUTHOR

Eric Dubois 2002