Hi there,
I have a time series with 40 obs. Based on the underlying process of the
series I would like to generate 5000 (for example) observations, so then I
can generate a robust (in the sense of being based on many observations)
concrete probability distribution . In order to do that what I though I could
do is:
- First, distribution testing of my original series, and then monte carlo
simulation.
Question: is there any command that allows me to test which is the best
distribution that fits my data, or do I need to test this distribution by
distribution (e.g. normality tests, chi-square...and so on).
- Is there any other command that allows me to generate observations (based
on the underlysing process of a time seies)?
(e.g. Can bsample, or bootstrap be of any help?)
Kind regards
Jose Seisdedos
Pension Analyst
OECD
DELSA
Annex Monaco R29
Mail correspondance:
2 Rue Andr�-Pascal
75775 Paris Cedex 16
FRANCE
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
