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st: AW: Bootstrapping new observations to add to an existing dataset


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: AW: Bootstrapping new observations to add to an existing dataset
Date   Mon, 22 Jun 2009 09:58:40 +0200

<> 

Without knowledge of the DGP, I imagine this to be hard. You can -bsample-, as pointed out by Carlo, but note that this would leave you with the same values as before: There will be no new observation, but some will occur in greater numbers than before - and some not at all.





HTH
Martin


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Davide Cantoni
Gesendet: Montag, 22. Juni 2009 05:58
An: statalist@hsphsun2.harvard.edu
Betreff: st: Bootstrapping new observations to add to an existing dataset

Hello, I am stuck while thinking about this issue and I would
appreciate your suggestions. I have a dataset which I use for
simulation purposes, to test whether my do-files run correctly. The
issue is that this dataset is too short for many applications, as it
has only 200 observations.

What I want to do is expand this dataset to include more observations,
but keeping the same (unknown to me) data generating process that
created the first 200 observations. So I was thinking to proceed in a
bootstrapping manner, by drawing the values for each one of the
variables (var1, var2 etc etc) for the new observations from the
empirical distributions of var1, var2,... in the first 200
observations. Yet, I have no idea on how to implement this. I'm
grateful for any idea. Thanks for your interest,

Davide
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