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 EffectsLevelization of Classification VariablesSpecification and Parameterization of Model EffectsEmpirical Distribution Function Estimation MethodsStatistics of FitDefining a Severity Distribution Model with the FCMP ProcedurePredefined Utility FunctionsScoring FunctionsCustom Objective FunctionsMultithreaded ComputationInput Data SetsOutput Data SetsDisplayed OutputODS Graphics
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ExamplesDefining a Model for Gaussian DistributionDefining a Model for the Gaussian Distribution with a Scale ParameterDefining a Model for Mixed-Tail DistributionsEstimating Parameters Using Cramér-von Mises EstimatorFitting a Scaled Tweedie Model with RegressorsFitting Distributions to Interval-Censored DataDefining a Finite Mixture Model That Has a Scale ParameterPredicting Mean and Value-at-Risk by Using Scoring FunctionsScale Regression with Rich Regression Effects
- References
You can use a series of programming statements that use variables in the input data set that you specify in the DATA= option in the PROC SEVERITY statement to assign a value to an objective function symbol. You must specify the objective function symbol by using the OBJECTIVE= option in the PROC SEVERITY statement. If you do not specify the OBJECTIVE= option in the PROC SEVERITY statement, then the programming statements are ignored and models are estimated using the maximum likelihood method.
You can use most DATA step statements and functions in your program. Any additional functions, restrictions, and differences are listed in the section Custom Objective Functions.