ols with t-distributed errors
[rolst]=olst(namey,arg1,...,argn)
* 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
* 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