Cochrane-Orcutt estimation of an autocorrelated model
rolsc=olsc1(y,x,maxit,crit)
* y = real (nx1) vector of an endogenous variable
* x = real (nxk) vector of an exogenous variable
* maxit = a scalar, the maximum # of authorized iterations
* crit = a scalar, the convergence criterionused to assess if the difference between successive values of the autocorrelation coefficient is significant
* rolsc = a results tlist with
- rolsc('meth') = 'Cochrane-Orcutt'
- rolsc('y') = y data vector
- rolsc('x') = x data matrix
- rolsc('nobs') = # observations
- rolsc('nvar') = # variables
- rolsc('beta') = bhat
- rolsc('yhat') = yhat
- rolsc('resid') = residuals
- rolsc('vcovar') = estimated variance-covariance matrix of beta
- rolsc('sige') = estimated variance of the residuals
- rolsc('sigu') = sum of squared residuals
- rolsc('ser') = standard error of the regression
- rolsc('tstat') = t-stats
- rolsc('pvalue') = pvalue of the betas
- rolsc('dw') = Durbin-Watson Statistic
- rolsc('condindex') = multicolinearity cond index
- rolsc('prescte') = boolean indicating the presence or absence of a constant in the regression
- rolsc('rsqr') = rsquared
- rolsc('rbar') = rbar-squared
- rolsc('f') = F-stat for the nullity of coefficients other than the constant
- rolsc('pvaluef') = its significance level
- rolsc('bounds') = if there is a timeseries in the regression, the bounds of the regression
- rolsc('rho') = estimated first order autocorrelation of residuals
- rolsc('trho') = its Student t
- rolsc('iterout') = a (niter x 3) matrix giving for each