 |
|
| The MDC Procedure |
| Functional Summary |
The statements and options used with the MDC procedure are summarized in the following table:
Description |
Statement |
Option |
|---|---|---|
Data Set Options |
||
formats the data for use by PROC MDC |
MDCDATA |
|
specify the input data set |
MDC |
DATA= |
write parameter estimates to an output data set |
MDC |
OUTEST= |
include covariances in the OUTEST= data set |
MDC |
COVOUT |
write linear predictors and predicted probabilities to an output data set |
OUTPUT |
OUT= |
Declaring the Role of Variables |
||
specify the ID variable |
ID |
|
specify BY-group processing variables |
BY |
|
Printing Control Options |
||
request all printing options |
MODEL |
ALL |
display correlation matrix of the estimates |
MODEL |
CORRB |
display covariance matrix of the estimates |
MODEL |
COVB |
display detailed information about optimization iterations |
MODEL |
ITPRINT |
suppress all displayed output |
MODEL |
NOPRINT |
Model Estimation Options |
||
specify the choice variables |
MODEL |
CHOICE=() |
specify the convergence criterion |
MODEL |
CONVERGE= |
specify the type of covariance matrix |
MODEL |
COVEST= |
specify the starting point of the Halton sequence |
MODEL |
HALTONSTART= |
specify options specific to the HEV model |
MODEL |
HEV=() |
set the initial values of parameters used by the iterative optimization algorithm |
MODEL |
INITIAL=() |
specify the maximum number of iterations |
MODEL |
MAXITER= |
specify the options specific to mixed logit |
MODEL |
MIXED=() |
specify the number of choices for each person |
MODEL |
NCHOICE= |
specify the number of simulations |
MODEL |
NSIMUL= |
specify the optimization technique |
MODEL |
OPTMETHOD= |
specify the type of random number generators |
MODEL |
RANDNUM= |
specify that initial values are generated using random numbers |
MODEL |
RANDINIT |
specify the rank dependent variable |
MODEL |
RANK |
specify optimization restart options |
MODEL |
RESTART=() |
specify a restriction on inclusive parameters |
MODEL |
SAMESCALE |
specify a seed for pseudo-random number generation |
MODEL |
SEED= |
specify a stated preference data restriction on inclusive parameters |
MODEL |
SPSCALE |
specify the type of the model |
MODEL |
TYPE= |
specify normalization restrictions on multinomial probit error variances |
MODEL |
UNITVARIANCE=() |
Controlling the Optimization Process |
||
specify upper and lower bounds for the parameter estimates |
BOUNDS |
|
specify linear restrictions on the parameter estimates |
RESTRICT |
|
specify nonlinear optimization options |
NLOPTIONS |
|
NESTED Logit Related Options |
||
specify the tree structure |
NEST |
LEVEL()= |
specify the type of utility function |
UTILITY |
U()= |
Output Control Options |
||
output predicted probabilities |
OUTPUT |
P= |
output estimated linear predictor |
OUTPUT |
XBETA= |
|
|
Copyright © 2008 by SAS Institute Inc., Cary, NC, USA. All rights reserved.