NLMOD Procedure
PROC NLMOD Statement
PROC NLMOD <options>;
The PROC NLMOD statement invokes the procedure. Table 1 summarizes important options in the PROC NLMOD statement by function. These and other options in the PROC NLMOD statement are then described fully in alphabetical order.
Table 1: PROC NLMOD Statement Options
| Option | Description |
|---|---|
| Basic Options | |
| DATA= | Specifies the input data table |
| OUT= | Specifies the output data table |
| Output Options | |
| CORR | Specifies the correlation matrix |
| COV | Specifies the covariance matrix |
| ECORR | Specifies the correlation matrix of additional estimates |
| ECOV | Specifies the covariance matrix of additional estimates |
| DF | Specifies the default degrees of freedom |
| NOPRINT | Suppresses ODS output |
| NOITPRINT | Suppresses output about iterations within the optimization process |
| Optimization Options | |
| ABSCONV= | Tunes an absolute function convergence criterion |
| ABSFCONV= | Tunes an absolute difference function convergence criterion |
| ABSGCONV= | Tunes the absolute gradient convergence criterion |
| FCONV= | Tunes the relative function convergence criterion |
| GCONV= | Tunes the relative gradient convergence criterion |
| MAXITER= | Chooses the maximum number of iterations in any optimization |
| MAXFUNC= | Specifies the maximum number of function evaluations in any optimization |
| MAXTIME= | Specifies the upper limit (in seconds) of CPU time for any optimization |
| MINITER= | Specifies the minimum number of iterations in any optimization |
| TECHNIQUE= | Selects the optimization technique |
| Tolerance Options | |
| SINGULAR= | Tunes the general singularity criterion |
The optimization options are fully described in the section Optimization Options in Chapter 2, Shared Concepts. Other options available in the PROC NLMOD statement are described in the following sections.
You can specify the following options in the PROC NLMOD statement:
-
ALPHA=
specifies the level of significance
that is used in constructing 
% confidence intervals. The value must be strictly between 0 and 1; the default value of 
results in 95% intervals. This value is used as the default confidence level for limits that are computed in the "Parameter Estimates" table and is used in the LOWER and UPPER options in the PREDICT statement. - CORR
requests the approximate correlation matrix for the parameter estimates.
- COV
requests the approximate covariance matrix for the parameter estimates.
- DATA=libref.data-table
-
names the input data table for PROC NLMOD 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.
- DF=n
specifies the default number of degrees of freedom to use in the calculation of p-values and confidence limits for additional parameter estimates.
- ECORR
requests the approximate correlation matrix for all expressions that are specified in ESTIMATE statements.
- ECOV
requests the approximate covariance matrix for all expressions that are specified in ESTIMATE statements.
- NOITPRINT
- NOPRINT
- OUT=libref.data-table
-
names the output data table for PROC NLMOD to use. 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 where the data table is to be stored. For more information about libref, see the section Using SAS Viya Workbench.- data-table
specifies the name of the output data table.
A single OUT= data table is created to contain all predicted values when more than one PREDICT statement is specified. An error message is generated if a PREDICT statement is specified and an OUT= data table is not specified. The variables in the input data table are not included in the output data table, in order to avoid data duplication for large data tables; however, variables that you specify in the ID statement are included.
- SINGULAR=number
tunes the general singularity criterion that is applied in sweeps and inversions. The default is
times the machine epsilon; this product is approximately 1E-12 on most computers.