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From |
"Glenn Goldsmith" <glenn.goldsmith@gmail.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: noisily summarize `lnf in ML Model' |

Date |
Sun, 12 Apr 2009 20:11:26 +0100 |

Hi, I'm afraid Quang's help request may not make a lot of sense to anybody other than Quang or me. Quang previously emailed me off-list, asking for help with an error he was receiving from -ml- "-<inf> could not be evaluated" I provided him with some general advice, including the fact that the error was likely due to missing `lnf' values, and suggested ways that he might try to track down the error. Now, if I understand correctly, he is receiving the error message: "numerical derivatives are approximate nearby values are missing" As the -summarize- results suggest, this is essentially the same problem, but with the missing `lnf' observations now only occurring for some parameter values. As such, I would simply reiterate my previous advice: If you can't figure out why [you might be getting missing `lnf' values] just by looking at the code, then you want to start looking at the values you use to calculate `lnf'. (a) -noisily summarize- all the variables/tempvars you use to calculate `lnf' just before the line where you calculate it. If any of them are missing, then this will be a source of problems. (b) -noisily display- any other scalars or macros you use in the calculation. Again, if any of them are missing, then it will also cause problems. (Though usually this would manifest itself in an error message.) If you discover something missing, then go back to where that is calculated and see if you can spot the problem there. If not, repeat (a) and (b) again there. If neither (a) nor (b) are the problem, then there's some sort of issue with the code you use to do the calculation. If you can't figure out what it is, try posting the line with the problem to the list again, and someone might be able to help you. The only thing I would add now is that, when trying to figure out what's going on, you probably want to be on the lookout for functions that return missing values only for some values of the arguments. E.g. if some parameter values result in your program trying to take the log of a non-positive number you'll get a missing value. I'd also emphasize that you're more likely to get useful responses the more specific you are about the nature of your problem. So, e.g. posting the relevant lines of your code would help. HTH, Glenn. Quang Nguyen <quangn@gmail.com> wrote: Dear All: To debug an ML program, I use noisily summarize `lnf'. Here is part of the report: Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- __000011 | 0 Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- __000011 | 4968 .6044496 .3089994 .0080576 .9919424 Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- __000011 | 3496 .5906751 .4917796 0 1 Since there is some zero observation in `lf', the "ml model" doesn't work. Can anyone suggest how I can proceed next given the above information? Many thanks! * * 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/

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