The SEVERITY Procedure
- Overview
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Getting Started
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Syntax
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DetailsPredefined DistributionsCensoring and TruncationParameter Estimation MethodParameter InitializationEstimating Regression EffectsEmpirical Distribution Function Estimation MethodsStatistics of FitDefining a Distribution Model with the FCMP ProcedurePredefined Utility FunctionsCustom Objective FunctionsMultithreaded ComputationInput Data SetsOutput Data SetsDisplayed OutputODS Graphics
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Examples
- References
Parameter Initialization
PROC SEVERITY enables you to initialize parameters of a model in different ways. There can be two kinds of parameters in a model: distribution parameters and regression parameters.
The distribution parameters can be initialized by using one of the following three methods:
- INIT= option
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You can use the INIT= option in the DIST statement.
- INEST= data set
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You can use the INEST= data set.
- PARMINIT subroutine
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You can define a dist_PARMINIT subroutine in the distribution model. See the section Defining a Distribution Model with the FCMP Procedure for more information.
Note that only one of the initialization methods is used. You cannot combine them. They are used in the following order:
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The method that uses the INIT= option takes the highest precedence. If you use the INIT= option to provide an initial value for at least one parameter, then other initialization methods (INEST= and PARMINIT) are not used. If you specify initial values for some but not all the parameters by using the INIT= option, then the uninitialized parameters are initialized to the default value of 0.001.
If this option is used when regression effects are specified, then the value of the first distribution parameter must be related to the initial value for the base value of the scale or log-transformed scale parameter. See the section Estimating Regression Effects for more information.
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The method that uses the INEST= data set takes the second precedence. If there is a nonmissing value specified for even one distribution parameter, then the PARMINIT method is not used and any uninitialized parameters are initialized to the default value of 0.001.
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If none of the distribution parameters are initialized by using the INIT= option or the INEST= data set, but the distribution model defines a PARMINIT subroutine, then PROC SEVERITY invokes that subroutine with appropriate inputs to initialize the parameters. If the PARMINIT subroutine returns missing values for some parameters, then those parameters are initialized to the default value of 0.001.
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If none of the initialization methods are used, each distribution parameter is initialized to the default value of 0.001.
See the section Estimating Regression Effects for more information about regression models and initialization of regression parameters.