Grocer Function
NAME
ols1a - ordinary least squares
CALLING SEQUENCE
[results]=ols1a(y,x,results)
PARAMETERS
Input
-
y = dependent variable vector (nobs x 1)
-
x = independent variables matrix (nobs x nvar)
-
results: an existing tlist of regression results
Output
-
a tlist with:
- results('meth') = 'ols'
- results('beta') = bhat
- results('tstat') = t-stats
- results('yhat') = yhat
- results('resid') = residuals
- results('sige') = e'*e/(n-k)
- results('rsqr') = rsquared
- results('rbar') = rbar-squared
- results('dw') = Durbin-Watson Statistic
- results('nobs') = nobs
- results('nvar') = nvars
- results('y') = y data vector
- results('x') = x data matrix
DESCRIPTION
One of the numerous functions performing ordinary least squares: this one assumes that x et y are already a matrix and a vector respectively, that a result tlist exists which can be filled and does not provide DW, Rē statistics.
EXAMPLE
1) r=ols1a(y,xd,rmod)
This example is taken from auto_stage0.
AUTHOR
Eric Dubois 2002