The HPSEVERITY Procedure
- Overview
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Getting Started
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Syntax
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DetailsPredefined DistributionsCensoring and TruncationParameter Estimation MethodDetails of Optimization AlgorithmsParameter InitializationEstimating Regression EffectsEmpirical Distribution Function Estimation MethodsStatistics of FitDistributed and Multithreaded ComputationDefining a Severity Distribution Model with the FCMP ProcedurePredefined Utility FunctionsScoring FunctionsCustom Objective FunctionsInput Data SetsOutput Data SetsDisplayed Output
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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 DistributionsFitting a Scaled Tweedie Model with RegressorsFitting Distributions to Interval-Censored DataBenefits of Distributed and Multithreaded ComputingEstimating Parameters Using Cramér-von Mises EstimatorDefining a Finite Mixture Model That Has a Scale ParameterPredicting Mean and Value-at-Risk by Using Scoring Functions
- References
PERFORMANCE options ;
The PERFORMANCE statement defines performance parameters for distributed and multithreaded computing, passes variables that describe the distributed computing environment, and requests detailed results about the performance characteristics of PROC HPSEVERITY.
You can also use the PERFORMANCE statement to control whether a high-performance analytical procedure executes in single-machine or distributed mode.
The PERFORMANCE statement is documented further in the section PERFORMANCE Statement of Chapter 3: Shared Concepts and Topics.