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 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