How to test linear restriction with both intercept and slope I have estimated the model
$y = \beta_{0} + \beta_{1}x + u$
I want to test the restriction that $\beta_{0} = 3$ and that $\beta_{1} = -2$. after setting both betas to their hypothesized values and rearranging, I get the equation:
$z = u$ where $z = y + 2x -3$
now I am lost as to how to actually run this regression because there are no independent variable and no intercept as well. if the value for the intercept was not restricted then i would simply define a new variable as $y + 2x$ and just compute it's ssr and use it to compute an F-statistics.

You can compute the sum of squared errors (or the likelihood in, say, a logistic regression case) and then conduct an $F$-test.  You'll probably have to do it manually.
$$
F = \frac{ \frac{SS_{resid,restricted}-SS_{resid,full}}{df_{resid,restricted}-df_{resid,full}}}
{\frac{SS_{resid,full}}{df_{resid,full}}}
$$
