Grocer Function

NAME

olst - ols with t-distributed errors

CALLING SEQUENCE

[rolst]=olst(grocer_namey,arg1,...,argn)

PARAMETERS

Input

Output

DESCRIPTION

Computes ols with t-distributed errors, using iterated re-weighted least-squares to find maximum likelihood estimates. Endogenous variable must be given first, 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

lresult = olst(y,x,'maxit=1000','crit=.0001');

This example, taken from olst_d, shows the estimation of a model where residuals are supposed to follow a Student law (in olst_d, the residuals are drawn from the Student law through the use of function tdis_rnd -see chapter 12 for a description of this function).

AUTHOR

Eric Dubois 2002