DOCUMENTATION
Sign In

Get access to My SAS, trials, communities and more.

Econometrics Procedures
 

SMC Procedure

EVALUATE Statement

  • EVALUATE <options>;

The EVALUATE statement specifies options that are related to the evaluation, which is the log-likelihood calculation (see the section SMC Evaluating). If you specify the LEARN statement, the model parameters in the requested evaluation process are set to the posterior mean of the corresponding model parameters; otherwise, the parameters with initial values that you specify in the PARAMETERS statement are used in the evaluation. You can specify the following options:

ALGORITHM=algorithm
ALG=algorithm

specifies the particle filter algorithm to use in the evaluation. You can specify the following algorithms:

APF<(ADP)>

specifies the auxiliary particle filter (APF) algorithm. The ADP suboption specifies the fully adapted auxiliary particle filter algorithm.

BF

specifies the bootstrap filter (BF) algorithm.

SIR<(TH | THRESH | THRESHOLD=number)>

specifies the sequential importance resampling (SIR) algorithm. The TH= option specifies the threshold (a value between 0 and 1) of the resampling step in the SIR algorithm. The resampling step occurs when the effective sample size is less than the product of the threshold and the number of particles. By default, TH=0.8.

By default, ALGORITHM=SIR.

NPARTICLE=number

specifies the number of particles (samples) to use in the evaluation. If you omit this option, the evaluation uses the value of the NPARTICLE= option in the PROC SMC statement.

OUT=libref.data-table

writes the evaluation estimates to an output data set. libref.data-table is a two-level name, where libref refers to the library, and data-table specifies the name of the output data table. For more information about this two-level name, see the DATA= option and the section Using CAS Sessions and CAS Engine Librefs.

PARM=MEAN | MEDIAN

specifies which parameter values from the posterior distribution to use for the evaluation problem when you also specify the LEARN statement. If you omit the LEARN statement, this option is ignored. You can specify one of the following values:

MEAN

solves the evaluation problem by using the estimated posterior means of the parameters.

MEDIAN

solves the evaluation problem by using the estimated posterior medians of the parameters.

By default, PARM=MEAN.

Last updated: July 09, 2026