The HPSEVERITY Procedure

Functional Summary

Table 5.1 summarizes the statements and options that control the HPSEVERITY procedure.

Table 5.1: HPSEVERITY Functional Summary

Description

Statement

Option

Statements

   

Specifies the response variable to model along with censoring and truncation effects

LOSS

 

Specifies the weight variable

WEIGHT

 

Specifies the regression variables to model

SCALEMODEL

 

Specifies distributions to fit

DIST

 

Specifies optimization options

NLOPTIONS

 

Specifies performance options

PERFORMANCE

Specifies programming statements that define an objective function

Programming statements

Data Set Options

   

Specifies that the OUTEST= data set contain covariance estimates

PROC HPSEVERITY

COVOUT

Specifies the input data set

PROC HPSEVERITY

DATA=

Specifies the input data set for parameter estimates

PROC HPSEVERITY

INEST=

Specifies the output data set for parameter estimates

PROC HPSEVERITY

OUTEST=

Specifies the output data set for model information

PROC HPSEVERITY

OUTMODELINFO=

Specifies the output data set for statistics of fit

PROC HPSEVERITY

OUTSTAT=

Data Interpretation Options

   

Specifies left-censoring

LOSS

LEFTCENSORED=

Specifies left-truncation

LOSS

LEFTTRUNCATED=

Specifies right-censoring

LOSS

RIGHTCENSORED=

Specifies right-truncation

LOSS

RIGHTTRUNCATED=

Model Estimation Options

   

Specifies the model selection criterion

PROC HPSEVERITY

CRITERION=

Specifies the method for computing mixture distribution

SCALEMODEL

DFMIXTURE=

Specifies initial values for model parameters

DIST

INIT=

Specifies the objective function symbol

PROC HPSEVERITY

OBJECTIVE=

Specifies the optimization technique

NLOPTIONS

TECHNIQUE=

Specifies the denominator for computing covariance estimates

PROC HPSEVERITY

VARDEF=

Optimization Termination Criteria

   

Absolute function value criterion

NLOPTIONS

ABSCONV=

Absolute function difference convergence criterion

NLOPTIONS

ABSFCONV=

Absolute gradient convergence criterion

NLOPTIONS

ABSGCONV=

Absolute parameter convergence criterion

NLOPTIONS

ABSXCONV=

Relative function convergence criterion

NLOPTIONS

FCONV=

Another relative function convergence criterion

NLOPTIONS

FCONV2=

Used in FCONV, GCONV criterion

NLOPTIONS

FSIZE=

Relative gradient convergence criterion

NLOPTIONS

GCONV=

Maximum number of function calls

NLOPTIONS

MAXFUNC=

Maximum number of iterations

NLOPTIONS

MAXITER=

Upper limit on CPU time in seconds

NLOPTIONS

MAXTIME=

Minimum number of iterations

NLOPTIONS

MINITER=

Relative parameter convergence criterion

NLOPTIONS

XCONV=

Used in XCONV criterion

NLOPTIONS

XSIZE=

Empirical Distribution Function (EDF) Estimation Options

   

Specifies the nonparametric method of CDF estimation

PROC HPSEVERITY

EMPIRICALCDF=

Specifies the sample to be used for computing the EDF estimates

PROC HPSEVERITY

INITSAMPLE

EMPIRICALCDF=MODIFIEDKM Options

   

Specifies the $\alpha $ value for the lower bound on risk set size

PROC HPSEVERITY

ALPHA=

Specifies the $c$ value for the lower bound on risk set size

PROC HPSEVERITY

C=

Specifies the absolute lower bound on risk set size

PROC HPSEVERITY

RSLB=

EMPIRICALCDF=TURNBULL Options

   

Specifies that the final EDF estimates be maximum likelihood estimates

PROC HPSEVERITY

ENSUREMLE

Specifies the relative convergence criterion

PROC HPSEVERITY

EPS=

Specifies the maximum number of iterations

PROC HPSEVERITY

MAXITER=

Specifies the threshold below which an EDF estimate is deemed to be 0

PROC HPSEVERITY

ZEROPROB=

Displayed Output Options

   

Specifies that distributions be listed to the log without estimating any models that use them

DIST

LISTONLY

Suppresses all displayed output

PROC HPSEVERITY

NOPRINT

Specifies which output to display

PROC HPSEVERITY

PRINT=

Specifies the verbosity of messages printed to the log

PROC HPSEVERITY

VERBOSE=

Specifies that distributions be validated without estimating any models that use them

DIST

VALIDATEONLY