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
