On Mon, 10 May 2010, RAZIA HAIDER wrote:
Thanks for quick reply. First i realized my basic mistakes :), now i
have
changed script, which is given below
scalar a = -0.5*log(2*pi)
scalar m=mean(vsat)
scalar mu=m/2
scalar sigma=m/mu
mle logl=a-log(sigma)-(sq1/sq)
series s=sigma^2
series sq=2*s
series s3=sigma^3
series c=vsat-mu
series sq1=c^2
params mu sigma
end mle --hessian
if I run this i have same error of "*The convergence criterion
was not met"* *But* if i choose in "preferences" L-BFGS-B , it
works properly and give me results.
I suspect you are initializing sigma very far away from the ML
estimate, so BFGS is having numerical trouble. L-BFGS-B will
sometimes work better under these conditions. (If "vsat" refers to
verbal SAT scores, the standard deviation will be in the hundreds,
far from the value of 2.0 that you set as a starting point.)
Another point is that estimating the variance parameter jointly
with the location parameter can, in general, be a difficult
numerical problem. It is common to concentrate the variance
parameter out of the loglikelihood to yield a more stable
calculation.
Allin Cottrell