Re: [Gretl-users] Missing values in MLE

Allin,    thanks a lot, that was the issue. When I thus try to constrain the calculation not to go in the direction where negative lambdas are created by    <hansl> function scalar getNegativesCount(series * xSeries)     scalar xRetVal = 0          loop xIdx = 1..$nobs         if missing( xSeries[xIdx] ) = 0             if xSeries[xIdx] < 0.0                 xRetVal = xRetVal + 1             endif         endif     endloop       return xRetVal end function ...# ESTIMATIONmle ll = xCheck == 0 ? -ln(lambda) - sqrtPark/lambda  : NA         series lambda = mean(sqrtPark)         series lambda = c_ + rng * sqrtPark(-1) + rng2 * sqrtPark(-2) + err_ * lambda(-1) + err_2 * lambda(-2)         scalar xCheck = getNegativesCount(& lambda)          params c_ rng rng2 err_ err_2end mle --robust#ESTIMATION</hansl>I get a "Scalar loglikelihood: can't do QML". So, how do I tell the optimizer that in case it runs to negative lambda, it should "go away" from that parameter combination? I also tried to replace the <hansl>...mle ll = xCheck == 0 ? -ln(lambda) - sqrtPark/lambda  : NA...</hansl>with <hansl>...mle ll = xCheck == 0 ? -ln(lambda) - sqrtPark/lambda  : -100000...</hansl>but it produced the same error.Many thanks, Daniel