Re: st: how to do subsampling in stata

[László Sándor <sandorl@gmail.com>]

Stas, I am not sure I'm with you on this one.

1. Subsampling looks much, much easier to implement than other novelties.
2. Many if not most people use bootstrap not because they derived that
their estimator is smooth but exactly because they worry that
something is not exactly canonical in their problem or application,
but hey, they can just bootstrap it. My admittedly limited
understanding of the difference between the two methods suggest that
subsampling is the safer bet.
3. The original (?) question on Statalist even mentioned that Abadie
and Imbens tried to warn people that matching is exactly a problem
where the bootstrap can be problematic, while subsampling they
recommend. With version 13, Stata became a matching powerhouse. Why
not support this simple thing, then?
http://www.stata.com/statalist/archive/2009-04/msg00920.html

Best,

Laszlo

On Thu, Aug 15, 2013 at 7:13 PM, Stas Kolenikov <skolenik@gmail.com> wrote:
> On Thu, Aug 15, 2013 at 12:12 PM, Phil Schumm <pschumm@uchicago.edu> wrote:
>> On Aug 15, 2013, at 11:45 AM, László Sándor <sandorl@gmail.com> wrote:
>>> Or of course, if StataCorp reading this is confident about how easy the transition from -bsample- to -sample- would be for a clone of -bootstrap-
>>
>> I'm not familiar with the literature on the subsampling, so what I'm about to say may not entirely apply here.  However, it is worth noting that a lot of what StataCorp does is not simply implementing estimators and methods, but is making sure that the theory behind them is sound, and that the various things users might do once the method is implemented in Stata are reasonable.  Thus, even though it might be fairly simple for a user to patch an existing command to accommodate a specific situation (for which they are willing to take full responsibility), it might take StataCorp longer to verify for themselves that the enhancement is really something with which they feel comfortable.
>
> Of many other wonderful theoretical developments in statistics and
> econometrics, why not (a) empirical likelihood and exponential
> tilting? (b) block bootstrap for time series? (c) delete-k jackknife
> for complex survey data? (d) degrees of freedom corrections in mixed
> models? (e) tetrad analysis in latent variable models? and an endless
> wish list follows. Each of these are well established in their
> specific literature, but their use is required in a fairly limited
> range of situations. It took Stata Corp about 10 years from seeing the
> first user-written multiple imputation and generalized linear latent
> variable and mixed model pacakges (-ice/mim- and -gllamm-, of course)
> to the production versions of these (-mi-, -meglm- and -gsem-), and
> these have three order of magnitude greater generalizability and
> potential user base than subsampling (which is really called for in
> weird situations with non-smooth estimators, so one needs to put a lot
> of work to even produce such an estimator) or empirical likelihood
> (which is asymptotically equivalent to the existing -gmm-, anyway).
>
> That's a long introduction to say that I would not expect to see Stata
> Corp working on this for the next three or so releases. If Laszlo's
> needs are more urgent, he should start working on his own
> implementation of subsampling. As I did with empirical likelihood :).
>
> -- Stas Kolenikov, PhD, PStat (ASA, SSC)
> -- Senior Survey Statistician, Abt SRBI
> -- Opinions stated in this email are mine only, and do not reflect the
> position of my employer
> -- http://stas.kolenikov.name
>
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