Hi,

I was wondering what is the best way to estimate the confidence of a likelihood estimate. I am doing a high throughput analysis, so I am looking for an automatic criterion. So far what I am doing is to pick in random the starting value of the parameters to estimate (e.g. P_0 = Random(0.0, 1.0), I optimize and repeat it N times. I keep the best likelihood score of N repeats and print a warning flag if the variance of likelihood score of N samples is too high.
Does it sound reasonable? ???

Thanks,

Olivier