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= How do I produce random variables which follow a negative skew distribution? =
 
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The below produces negatively skewed data with no upper bound.

{{{
define !gamma ( !pos !tokens(1)
                /!pos !tokens(1)).
!do !i=!1 !to !2 !by 1.
compute !concat(a,!i)=-(10000)*ln(rv.uniform(0,1)*10000).
!doend.
!enddefine.

!gamma 1 2.
exe.

compute sum=0.
exe.


compute sum=-(a1+a2).
exe.
}}}

How do I produce random variables which follow a negative skew distribution?

Most distributions such as the exponential and log-Normal distributions are positive skewed with the model of the distribution for lower values.

[http://www.uib.no/people/ngbnk/kurs/notes/node31.html The Gamma distribution] which has two parameters, $$\alpha$$ and $$\beta$$ may produce negative skew where the model occurs for higher values (values > 0) when $$/alpha$$ is a lot greater than $$\beta$$. It also has no maximum value.

The below produces negatively skewed data with no upper bound.

define !gamma ( !pos !tokens(1)
                /!pos !tokens(1)).
!do !i=!1 !to !2 !by 1.
compute !concat(a,!i)=-(10000)*ln(rv.uniform(0,1)*10000).
!doend.
!enddefine.

!gamma 1 2.
exe.

compute sum=0.
exe.


compute sum=-(a1+a2).
exe.

None: FAQ/gamma (last edited 2013-03-08 10:17:36 by localhost)