Re: st: Computation Speed for Bootstrapping

[Danny Dan <danny2011dan@gmail.com>]

Thank you so much Ben for replying to my query. I have tried
implementing your's and Jeph's suggestions but now it is giving me the
following error r(2000):

insufficient observations to compute bootstrap standard errors
no results will be saved

However, without those additional commands my bootstrap is running,
although the computation is extremely slow (taking almost 4 days for
only 50 reps. My data set contains 10,000 obs.).

Also do you or any statalist users have any idea why the problem
r(2000) (insufficient observations to compute bootstrap standard
errors, no results will be saved) occurs and how to fix it? If yes,
then please let me know.

Thanks and Best wishes.

Dan



On Fri, Dec 2, 2011 at 5:08 AM, Benjamin Volland <volland@econ.mpg.de> wrote:
> Hi Danny,
>
> your most easy option is to follow Jeph's second suggestion.
> That is, run your estimation once on the full sample. Then use
> - matrix b = e(b) - and then simply re-use the same matrix as starting
> values for each bootstrap iteration, using the -from(b)- option in your
> -xtprobit- command.
> You'll probably have to check whether this increases estimation speed
> substantially using a small number of bootstrap interations, and simply
> compare the time with and without setting initial values.
> If you want to use different starting values in each iteration (though I
> somehow fail to see the improvement given that each bootstrap iteration
> simply draws a new sample from the original data), i.e.
> write your own bootstrap program, check the Sata FAQ from the UCLA on how to
> do it:
> http://www.ats.ucla.edu/stat/stata/faq/ownboot.htm
> Again, whether that substantially increases the speed of your estimation you
> would have to check.
>
> Best, Ben
>
>
>
> On 01/12/2011 23:41, Danny Dan wrote:
>>
>> Thank you so much for the answer Jeph. However, I do not know how to
>> write the code as mentioned in your reply. If you can give me further
>> insight that would be really helpful.
>>
>> Thanks once again.
>>
>> On Sun, Nov 27, 2011 at 10:06 AM, Jeph Herrin<stata@spandrel.net>  wrote:
>>>
>>> One trick is to re-use the estimation from each model as the starting
>>> values
>>> for the next one. So after calling xtprobit, save the matrix e(b) and
>>> then
>>> use it with the -from(b)- option.
>>>
>>>   xtprobit ...
>>>   matrix b=e(b)
>>>   xtprobit ...., from(b)
>>>
>>> But to do this, I think you'll have to write your own bootstrap code (not
>>> too difficult).
>>> Or you may get by with using -bootstrap:-, if you reuse the same matrix
>>> for
>>> each
>>> bootstrap.
>>>
>>> Hope this helps,
>>> Jeph
>>>
>>>
>>>
>>> On 11/26/2011 10:31 PM, Danny Dan wrote:
>>>>
>>>>
>>>> Dear All,
>>>>
>>>> How to increase computation speed while generating standard errors
>>>> using bootstrapping for panel data probit model (xtprobit,
>>>> vce(bootstrap))?
>>>>
>>>> Reduction in the number of replications (reps()) is of no help.
>>>>
>>>> Please let me know.
>>>>
>>>> Thank you,
>>>>
>>>> Regards,
>>>>
>>>> Malini
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