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I am dealing with an example stated in here.

Given the same data in the above link and following a parametric bootstrap method suggested in here, I computed the standard errors for maximum likelihood estimates (the method suggested there worked perfectly well! Thank you!).

But I would like to compare the result from this parametric bootstrapping with something else. Does anyone have some alternative(s) to compute the standard errors for the maximum likelihood estimates in the current example? Thank you very much for your help in advance!

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    @Szabolcs: Thank you very much for your prompt response and let me apologize for a (possibly) misdirected question. I do not mind if the webmaster remove this question due to the inappropriateness of the question. Sorry again. –  Jun 19 '14 at 18:31
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    No need to apologize. This is a good question, and it will *not be removed*. It will simply be *migrated* to another website where you will likely receive better answers than what you would receive here. – Szabolcs Jun 19 '14 at 18:32
  • @Szabolcs: Thank you very much for your understanding! –  Jun 19 '14 at 18:39

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