My question is why I'm not getting the correct variance-covariance
matrix in the example below (simple linear regression) when using
optimize_result_V(S).
Any thoughts on this?
Nicola
/* Linear regression using Mata optimize */
sysuse auto, clear
local xlist mpg cons
mata
st_view(x=0,.,("mpg"))
st_view(y=0,.,("price"))
x=x,J(rows(x),1,1)
void olsest(todo, b, y, x, lf, g, H)
{
e = (y-x*b')
lf = -(e'*e)
}
S = optimize_init()
optimize_init_evaluator(S, &olsest())
optimize_init_evaluatortype(S, "v0")
optimize_init_argument(S, 1, y)
optimize_init_argument(S, 2, x)
optimize_init_params(S, J(1,cols(x),0))
optimize_init_which(S,"max")
betahat = optimize(S)
vhat = optimize_result_V(S)
st_matrix("b", betahat)
st_matrix("V", vhat)
end
matrix colnames b = `xlist'
matrix colnames V = `xlist'
matrix rownames V = `xlist'
ereturn post b V , dep(price)
ereturn di
reg price mpg
exit
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
