Grocer Function
NAME
olst - ols with t-distributed errors
CALLING SEQUENCE
[rolst]=olst(grocer_namey,arg1,...,argn)
PARAMETERS
Input
-
grocer_namey = a time series, a real (nx1) vector or a string equal to the name of a time series or a (nx1) real vector between quotes
-
argi = an argument which can be:
- a time series
- a real (nx1) vector
- a real (nxk) matrix
- a string equal to the name of a time series or a (nxk) real vector or matrix between quotes
- a list of such elements
- the string 'noprint' if the user doesn't want to display the results of the regression
Output
-
rolst = a tlist with
- rolst('meth') = 'olst'
- rolst('y') = y data vector
- rolst('x') = x data matrix
- rolst('nobs') = nobs
- rolst('nvar') = nvars
- rolst('beta') = bhat
- rolst('yhat') = yhat
- rolst('resid') = residuals
- rolst('vcovar') = estimated variance-covariance matrix of beta
- rolst('sige') = estimated variance of the residuals
- rolst('ser') = standard error of the regression
- rolst('tstat') = t-stats
- rolst('pvalue') = pvalue of the betas
- rolst('dw') = Durbin-Watson Statistic
- rolst('namey') = name of the y variable
- rolst('namex') = name of the x variables
- rolst('bounds') = if there is a timeseries in the regression, the bounds of the regression
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