I am doing bootstraps by rerunning proc model for 1000 randomly selected samples.
It's a system of equations estimated by GMM and the object of interest is the "objective value"
(actually objective*N), which is Hansen's J statistic. I want to save this to an output file at
each bootstrap iteration.
I cannot find how to do this in any of the SAS documentation.
I'm running SAS 9.4.
Hello,
Do you have a SOLVE statement?
SOLVE variables <SATISFY= equations> </options>;
I think the options that you need are:
OUT=SAS-data-set
Only the solution values are output by default.
OUTACTUAL
outputs the actual values of the solved variables read from the input data set to the OUT= data set. This option is applicable only if the OUT= option is specified.
OUTOBJVALS
writes the objective function value to the OBJVALS variable in the OUT= data set. The objective function value is computed only when the OPTIMIZE solution method is specified. This value is close to 0 when an unbounded simultaneous solution is computed and can be greater than 0 when bounds are active in the solution. This option applies only if the OUT= option is specified.
OUTPREDICT
writes the solution values to the OUT= data set. This option applies only if the OUT= option is specified.
The OUTPREDICT option is the default unless one of the other output options is specified.
Koen
Latest 9.4 documentation
on Hansen’s J test statistic
SAS/ETS 15.1
https://support.sas.com/documentation/onlinedoc/ets/151/model.pdf
p.1495
p.1744: reference to Hansen, L. P. publications.
You are interested in:
the object of interest is the "objective value"(actually objective*N), which is Hansen's J statistic.
Do you have this statistic in a table for the last bootstrap iteration (nbr. 1000)?
Are you missing the first 999 values
or don't you have anything?
Cheers,
Koen
That did not work; I'm using a FIT statement - not a SOLVE stement.
However, this did:
"ods output GMMTestStats=GMMST;"
Adding this ODS statement before the Proc Model step outputs exactly what I need to a data file.
Build your skills. Make connections. Enjoy creative freedom. Maybe change the world. Registration is now open through August 30th. Visit the SAS Hackathon homepage.
Register today!Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.