Date: Wed, 24 Aug 2005 22:48:33 -0700
Reply-To: David L Cassell <davidlcassell@MSN.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: David L Cassell <davidlcassell@MSN.COM>
Subject: Re: Question: Underlying distributions in monte carlo simulation.
Content-Type: text/plain; format=flowed
>I'm currently running this command in SAS:
>DATA DRAWS (keep = FIPS DRAW_P_STD--LN_DRAW_CDD I);
> set WXDATA;
> DO I=1 TO &NumofDraws.;
> ****NORMAL DRAWS*****;
> Draw_P_STD=P_STD_Mean+sqrt(P_STD_Vari)*rannor(0); *****Zero pegs seed at
>time of day. See SAS notes on RANNOR fcn.;
> *****LOGNORMAL DRAWS*****;
>My question is this: Is there a way to plug in the skew and kurtosis into a
>random draw command (i.e. similar to rannor, but obviously better able to
>change the distribution's shape from normal). Previous posts point to
>reading in a PDF input dataset (i.e. bins with percentages) and using that
>for the underlying distribution for the draw. Any thoughts/ideas are
Working from an artificially-constructed pdf or cdf seems like a reasonable
Here are a couple more suggestions you might try.
 Consider starting with a 3-parameter or 4-parameter generalized gamma
distribution. You may be able to find formulae for the first four moments
and back-calculate to appropriate values of the parameters before doing
 Consider using a mixture distribution. If you start with a mixture of
k normal distributions (where k is something simple, like 2 or 3) and you
the mixture, then you can try to control the skewness and kurtosis of the
David L. Cassell
3115 NW Norwood Pl.
Corvallis OR 97330
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