PHSELECT Procedure

PROC PHSELECT Statement

  • PROC PHSELECT <options>;

The PROC PHSELECT statement invokes the procedure. Table 1 summarizes the available options in the PROC PHSELECT statement by function. They are then described fully in alphabetical order.

Table 1: PROC PHSELECT Statement Options

Option Description
ALPHA= Specifies a global significance level
DATA= Specifies the input data table
MULTIPASS= Specifies whether to levelize the data table every time it is read
Output Options
CORRB Displays the "Parameter Estimates Correlation Matrix" table
COVB Displays the "Parameter Estimates Covariance Matrix" table
ITHIST Displays the "Iteration History" table
LOGLIKENULL Displays the "–2 Log Likelihood for Null Model" table
NOCLPRINT Limits or suppresses the display of class levels
NOSTDERR Suppresses computation of the covariance matrix and standard errors
Optimization Options
ABSCONV= Tunes the absolute function convergence criterion
ABSFCONV= Tunes the absolute function difference convergence criterion
ABSGCONV= Tunes the absolute gradient convergence criterion
ABSXCONV= Tunes the absolute parameter convergence criterion
FCONV= Tunes the relative function difference convergence criterion
FCONV2= Tunes the second relative function difference convergence criterion
GCONV= Tunes the relative gradient convergence criterion
GCONV2= Tunes the second relative gradient convergence criterion
XCONV= Tunes the relative gradient convergence criterion
HESSIAN Uses analytic Hessian instead of finite-difference Hessian
MAXFUNC= Specifies the maximum number of function evaluations in any optimization
MAXITER= Specifies the maximum number of iterations in any optimization
MAXTIME= Specifies the upper limit of CPU time (in seconds) for any optimization
MINITER= Specifies the minimum number of iterations in any optimization
TECHNIQUE= Selects the optimization technique
LASSO Options
LASSORHO= Specifies the base regularization parameter for the LASSO method
LASSOSTEPS= Specifies the maximum number of steps for the LASSO method
LASSOTOL= Specifies the convergence criterion for the LASSO method


The optimization options, with the exception of the HESSIAN option, are fully described in the section Optimization Options in Chapter 2, Shared Concepts. The following list describes the other options available in the PROC PHSELECT statement:

ALPHA=number

specifies a global significance level for the construction of confidence intervals. The confidence level is 1–number. The value of number must be between 0 and 1. By default, ALPHA=0.05.

CORRB

creates the "Parameter Estimates Correlation Matrix" table. The correlation matrix is computed by normalizing the covariance matrix . That is, if is an element of , then the corresponding element of the correlation matrix is , where .

COVB

creates the "Parameter Estimates Covariance Matrix" table. The covariance matrix is computed as the inverse of the negative Hessian matrix, which is the matrix of second derivatives of the log-likelihood function with respect to the model parameters.

DATA=libref.data-table

names the input data table for PROC PHSELECT to use. The default is the most recently created data table. libref.data-table is a two-level name, where

libref

refers to a collection of information that is defined in the LIBNAME statement and includes the library, which includes a path to the data. For more information about libref, see the section Using SAS Viya Workbench.

data-table

specifies the name of the input data table.

HESSIAN

computes the Hessian matrix by using the analytic expression for the second-order derivatives of the log partial likelihood function instead of using the finite-difference method. When you specify this option, the optimization technique defaults to the Newton-Raphson method with ridging (TECH=NRRIDG), but you can use the TECH= option to specify the technique of your choice. The HESSIAN option requires a large amount of memory for each machine in the cluster.

ITHIST

generates the "Iteration History" table.

LASSORHO=r

specifies the base regularization parameter for the LASSO model selection method. The regularization parameter for step i is r. By default, LASSORHO=0.8.

LASSOSTEPS=n

specifies the maximum number of steps for LASSO model selection. By default, LASSOSTEPS=20.

LASSOTOL=r

specifies the convergence tolerance for the optimization algorithm that solves for the LASSO parameter estimates at each step of LASSO model selection. By default, LASSOTOL=1E–6.

LOGLIKENULL

creates the "–2 Log Likelihood for the Null Model" table. If you also specify the PARTITION statement, the table displays the –2 log likelihood for the null model for each data partition.

MULTIPASS=TRUE | FALSE

specifies when to levelize the data table—that is, when to generate the design rows for your model from the data. This option does not affect how the OUTPUT statement is processed. You can specify the following values:

TRUE

levelizes the data every time they are read. This method is slower but uses less memory.

FALSE

levelizes the data once and stores them in a temporary data table, then rereads the data from that table as needed. This method is faster but uses more memory.

By default, MULTIPASS=FALSE.

NOCLPRINT<=number>

suppresses the display of the "Class Level Information" table if you do not specify number. If you specify number, the values of the classification variables are displayed for only those variables whose number of levels is less than number. Specifying number helps reduce the size of the "Class Level Information" table if some classification variables have a large number of levels.

NOSTDERR

suppresses computation of the covariance matrix and the standard errors of the regression coefficients. When the model contains many variables (such as thousands), inverting the Hessian matrix to derive the covariance matrix and the standard errors of the regression coefficients can be time-consuming. The CORRB, COVB, and TYPE3 options are not available when you specify this option.

Last updated: May 14, 2026