Table 9.1 summarizes the statements and options that control the HPSEVERITY procedure.
Table 9.1: HPSEVERITY Functional Summary
Description |
Statement |
Option |
---|---|---|
Statements |
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Specifies BY-group processing |
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Specifies the response variable to model along with censoring and truncation effects |
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Specifies the weight variable |
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Specifies the regression variables to model |
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Specifies distributions to fit |
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Specifies the library to write scoring functions to |
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Specifies optimization options |
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Specifies performance options |
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Specifies programming statements that define an objective function |
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Data Set Options |
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Specifies that the OUTEST= data set contain covariance estimates |
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Specifies the input data set |
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Specifies the input data set for parameter estimates |
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Specifies the output data set for parameter estimates |
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Specifies the output data set for model information |
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Specifies the output data set for statistics of fit |
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Data Interpretation Options |
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Specifies left-censoring |
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Specifies left-truncation |
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Specifies right-censoring |
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Specifies right-truncation |
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Model Estimation Options |
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Specifies the model selection criterion |
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Specifies the method for computing mixture distribution |
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Specifies initial values for model parameters |
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Specifies the objective function symbol |
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Specifies the offset variable in the scale regression model |
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Specifies the optimization technique |
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Specifies the denominator for computing covariance estimates |
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Optimization Termination Criteria |
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Absolute function value criterion |
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Absolute function difference convergence criterion |
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Absolute gradient convergence criterion |
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Absolute parameter convergence criterion |
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Relative function convergence criterion |
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Another relative function convergence criterion |
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Used in FCONV, GCONV criterion |
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Relative gradient convergence criterion |
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Maximum number of function calls |
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Maximum number of iterations |
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Upper limit on CPU time in seconds |
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Minimum number of iterations |
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Relative parameter convergence criterion |
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Used in XCONV criterion |
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Empirical Distribution Function (EDF) Estimation Options |
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Specifies the nonparametric method of CDF estimation |
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Specifies the sample to be used for computing the EDF estimates |
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EMPIRICALCDF=MODIFIEDKM Options |
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Specifies the value for the lower bound on risk set size |
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Specifies the value for the lower bound on risk set size |
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Specifies the absolute lower bound on risk set size |
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EMPIRICALCDF=TURNBULL Options |
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Specifies that the final EDF estimates be maximum likelihood estimates |
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Specifies the relative convergence criterion |
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Specifies the maximum number of iterations |
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Specifies the threshold below which an EDF estimate is deemed to be 0 |
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Scoring Function Generation Options |
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Specifies that scoring functions of all models be written to one package |
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Specifies the output data set for BY-group identifiers |
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Specifies the output library for scoring functions |
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Displayed Output Options |
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Specifies that distributions be listed to the log without estimating any models that use them |
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Suppresses all displayed output |
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Specifies which output to display |
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Specifies the verbosity of messages printed to the log |
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Specifies that distributions be validated without estimating any models that use them |