The NLMOD Procedure

PROC NLMOD Statement

PROC NLMOD <options>;

The PROC NLMOD statement invokes the procedure. Table 14.1 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 14.1: 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 3: 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=CAS-libref.data-table

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

CAS-libref: refers to a collection of information that is defined in the LIBNAME statement and includes the caslib, which includes a path to the data, and a session identifier, which defaults to the active session but which can be explicitly defined in the LIBNAME statement. For more information about CAS-libref, see the section Using CAS Sessions and CAS Engine Librefs.
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

suppresses the display of the "Iteration History" table.

NOPRINT

suppresses the generation of ODS output.

OUT=CAS-libref.data-table

names the output data table for PROC NLMOD to use. CAS-libref.data-table is a two-level name, where

CAS-libref: refers to a collection of information that is defined in the LIBNAME statement and includes the caslib, which includes a path to where the data table is to be stored, and a session identifier, which defaults to the active session but which can be explicitly defined in the LIBNAME statement. For more information about CAS-libref, see the section Using CAS Sessions and CAS Engine Librefs.
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.

Last updated: December 21, 2018