|
Size: 859
Comment:
|
Size: 689
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 1: | Line 1: |
| = How do I produce random variables which follow a negative skew distribution? = | = How do I produce random variables which follow a negatively skewed distribution? = |
| Line 3: | Line 3: |
| Most distributions such as the exponential and log-Normal distributions are positively skewed with the mode of the distribution occurring for lower values. | |
| Line 4: | Line 5: |
| Most distributions such as the exponential and log-Normal distributions are positive skewed with the model of the distribution for lower values. | The Weibull distribution is negatively skewed and may be generated [http://www.taygeta.com/random/weibull.xml using random variables which are uniform on the interval [0,1]] The below produces an open ended negatively skewed weibull distribution with parameters, 2 and 20. It has a median of $$ 2^text{-0.05}((ln(2)^text{0.05})) = \mbox{approx. 0.95.} $$ |
| Line 7: | Line 14: |
| [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. |
|
| Line 12: | Line 15: |
| 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). |
compute wrv= (-(1/2)*(ln(1-rv.uniform(0,1))))**(0.05). |
How do I produce random variables which follow a negatively skewed distribution?
Most distributions such as the exponential and log-Normal distributions are positively skewed with the mode of the distribution occurring for lower values.
The Weibull distribution is negatively skewed and may be generated [http://www.taygeta.com/random/weibull.xml using random variables which are uniform on the interval [0,1]]
The below produces an open ended negatively skewed weibull distribution with parameters, 2 and 20. It has a median of
$$ 2text{-0.05}((ln(2)text{0.05})) = \mbox{approx. 0.95.} $$
compute wrv= (-(1/2)*(ln(1-rv.uniform(0,1))))**(0.05). exe.