The SEVERITY Procedure
- Overview
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Getting Started
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Syntax
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Details
Predefined Distributions Censoring and Truncation Parameter Estimation Method Parameter Initialization Estimating Regression Effects Empirical Distribution Function Estimation Methods Statistics of Fit Defining a Distribution Model with the FCMP Procedure Predefined Utility Functions Custom Objective Functions Input Data Sets Output Data Sets Displayed Output ODS Graphics
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Examples
Defining a Model for Gaussian Distribution Defining a Model for Gaussian Distribution with a Scale Parameter Defining a Model for Mixed-Tail Distributions Estimating Parameters Using Cramér-von Mises Estimator Fitting a Scaled Tweedie Model with Regressors Fitting Distributions to Interval-Censored Data
- References
| SCALEMODEL Statement |
The SCALEMODEL statement specifies regression variables. All the variables specified in this statement must be present in the input data set that is specified by the DATA= option in the PROC SEVERITY statement. The scale parameter of each candidate distribution is linked to a linear combination of these regression variables along with an intercept. If a distribution does not have a scale parameter, then a model based on that distribution is not estimated. If you specify more than one SCALEMODEL statement, then the first statement is used.
The regressor variables are expected to have nonmissing values. If any of the variables has a missing value in an observation, then a warning is written to the SAS log and that observation is ignored.
More details about modeling regression effects are provided in the section Estimating Regression Effects.