## Parametric CDF

You can fit the normal, lognormal, exponential,
and Weibull distributions to your data.
You specify the family of distributions either
in the cumulative distribution options dialog or
from the **Parametric CDF Estimation** dialog after
choosing **Curves:Parametric CDF** from the menu.

**Figure 38.29:** Parametric CDF Dialog

For the normal distribution, you can specify your own and parameters from the **Fit Parametric** menu.
Otherwise, you can use the sample mean and standard deviation
as estimates for and by selecting
**Fit Parametric:Normal** in the cumulative distribution options dialog
or by choosing **Distribution:Normal** and
**Method:Sample Estimates/MLE**
in the **Parametric CDF Estimation** dialog.
For the lognormal, exponential, and Weibull distributions,
you can specify your own threshold parameter and have the remaining parameters estimated by the maximum-
likelihood method, or you can specify all the distribution
parameters in the **Parametric CDF Estimation** dialog.
Otherwise, you can have the threshold parameter
set to 0 and the remaining parameters estimated
by the maximum-likelihood method.
To do this, select **Lognormal**, **Exponential**, or **Weibull**
in the Cumulative Distribution Output dialog or choose
**Method:Sample Estimates/MLE** and **Parameter:MLE, Theta:0**
in the **Parametric CDF Estimation** dialog.
If you select a **Weight** variable, only normal CDF can be created.
For **Method:Sample Estimates/MLE**,
and *s*_{w}
are used to display the cumulative distribution function
with vardef=**WDF/WGT**;
and *s*_{a}
are used with vardef=**DF/N**.
For **Method:Specification**, the values in the entry fields
**Mean/Theta** and **Sigma** are used to display the
cumulative distribution function with vardef=**WDF/WGT**;
the values of **Mean/Theta** and **Sigma**/are used with vardef=**DF/N**.

Figure 38.30 displays a normal distribution
function with = 58.4333 (the sample mean) and
= 8.2807 (the sample standard deviation);
it also displays a lognormal distribution function with
= 30 and and estimated by the MLE.

**Figure 38.30:** Parametric CDF

Use sliders to change the CDF estimate.
When MLE is used for the lognormal, exponential, and
Weibull distributions, changing the value of in the slider also causes the remaining parameters
to be estimated by the MLE for the new .

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.