Functional Summary
The statements and options used with the AUTOREG procedure are summarized in the
following table.
Table 8.1 AUTOREG Functional Summary
Description
Statement
Option
Data Set Options
Specify the input data set
AUTOREG DATA=
Write parameter estimates to an output
AUTOREG OUTEST=
data set
Include covariances in the OUTEST=
AUTOREG COVOUT
data set
Requests that the procedure produce
AUTOREG PLOTS=
graphics via the Output Delivery System
Write predictions, residuals, and
OUTPUT
OUT=
confidence limits to an output data set
Declaring the Role of Variables
Specify BY-group processing
BY
Specify classification variables
CLASS
Printing Control Options
Request all printing options
MODEL
ALL
Print transformed coefficients
MODEL
COEF
Print correlation matrix of the estimates MODEL
CORRB
Print covariance matrix of the estimates MODEL
COVB
Print DW statistics up to order
MODEL
DW=
Print marginal probability of the
generalized Durbin-Watson test statistics MODEL
DWPROB
for large sample sizes
Print the p-values for the Durbin-Watson
test be computed using a linearized
MODEL
LDW
approximation of the design matrix
Print inverse of Toeplitz matrix
MODEL
GINV
Print the Godfrey LM serial correlation
MODEL
GODFREY=
test
Print details at each iteration step
MODEL
ITPRINT
Print the Durbin t statistic
MODEL
LAGDEP
Print the Durbin h statistic
MODEL
LAGDEP=
Print the log-likelihood value of the
MODEL
LOGLIKL
regression model
Print the Jarque-Bera normality test
MODEL
NORMAL
Print the tests for the absence of ARCH
MODEL
ARCHTEST=
effects
Print BDS tests for independence
MODEL
BDS=
Print rank version of von Neumann ratio
MODEL
VNRRANK=
test for independence
Print runs test for independence
MODEL
Print the turning point test for
MODEL
independence
Print the Lagrange multiplier test
HETERO
Print the Chow test
MODEL
Print the predictive Chow test
MODEL
Suppress printed output
MODEL
Print partial autocorrelations
MODEL
Print Ramsey’s RESET test
MODEL
Print Phillips-Perron tests for stationarity
MODEL
or unit roots
Print Augmented Dickey-Fuller tests for
MODEL
stationarity or unit roots
Print ERS tests for stationarity or unit
MODEL
roots
Print Ng-Perron tests for stationarity or
MODEL
unit roots
Print KPSS tests for stationarity or unit
MODEL
roots
Print tests of linear hypotheses
TEST
Specify the test statistics to use
TEST
Print the uncentered regression
MODEL
Options to Control the Optimization Process
Specify the optimization options
Model Estimation Options
Specify the order of autoregressive
process
Center the dependent variable
Suppress the intercept parameter
Remove nonsignificant AR parameters
Specify significance level for
BACKSTEP
Specify the convergence criterion
Specify the type of covariance matrix
Set the initial values of parameters used
by the iterative optimization algorithm
Specify iterative Yule-Walker method
Specify maximum number of iterations
Specify the estimation method
Use only first sequence of nonmissing
data
Specify the optimization technique
Imposes restrictions on the regression
estimates
Estimate and test heteroscedasticity
models
RUNS=
TP=
TEST=LM
CHOW=
PCHOW=
NOPRINT
PARTIAL
RESET
STATIONARITY=(PHILLIPS=)
STATIONARITY=(ADF=)
STATIONARITY=(ERS=)
STATIONARITY=(NP=)
STATIONARITY=(KPSS=)
TYPE=
URSQ
NLOPTIONS
see Chapter 6, Nonlinear
Optimization Methods,
MODEL
NLAG=
MODEL
MODEL
MODEL
CENTER
NOINT
BACKSTEP
MODEL
SLSTAY=
MODEL
MODEL
CONVERGE=
COVEST=
MODEL
INITIAL=
MODEL
MODEL
MODEL
ITER
MAXITER=
METHOD=
MODEL
NOMISS
MODEL
OPTMETHOD=
RESTRICT
HETERO
GARCH Related Options
Specify order of GARCH process
Specify type of GARCH model
Specify various forms of the GARCH-M
model
Suppress GARCH intercept parameter
Specify the trust region method
Estimate the GARCH model for the
conditional t distribution
Estimate the start-up values for the
conditional variance equation
Specify the functional form of the
heteroscedasticity model
Specify that the heteroscedasticity model
does not include the unit term
Impose constraints on the estimated
parameters in the heteroscedasticity
model
Impose constraints on the estimated
standard deviation of the
heteroscedasticity model
Output conditional error variance
Output conditional prediction error
variance
Specify the flexible conditional variance
form of the GARCH model
Output Control Options
Specify confidence limit size
Specify confidence limit size for
structural predicted values
Specify the significance level for the
upper and lower bounds of the CUSUM
and CUSUMSQ statistics
Specify the name of a variable to contain
the values of the Theil’s BLUS residuals
Output the value of the error variance
Output transformed intercept variable
Specify the name of a variable to contain
the CUSUM statistics
Specify the name of a variable to contain
the CUSUMSQ statistics
Specify the name of a variable to contain
the upper confidence bound for the
CUSUM statistic
Specify the name of a variable to contain
the lower confidence bound for the
CUSUM statistic
MODEL
MODEL
GARCH=(Q=,P=)
GARCH=( ,TYPE=)
MODEL
GARCH=( ,MEAN=)
MODEL
MODEL
GARCH=( ,NOINT)
GARCH=( ,TR)
MODEL
GARCH=( ) DIST=
MODEL
GARCH=( ,STARTUP=)
HETERO
LINK=
HETERO
NOCONST
HETERO
COEF=
HETERO
STD=
OUTPUT
CEV=
OUTPUT
CPEV=
HETERO
OUTPUT
ALPHACLI=
OUTPUT
ALPHACLM=
OUTPUT
ALPHACSM=
OUTPUT
BLUS=
OUTPUT
OUTPUT
CEV=
CONSTANT=
OUTPUT
CUSUM=
OUTPUT
CUSUMSQ=
OUTPUT
CUSUMUB=
OUTPUT
CUSUMLB=
Specify the name of a variable to contain
the upper confidence bound for the
CUSUMSQ statistic
Specify the name of a variable to contain
the lower confidence bound for the
CUSUMSQ statistic
Output lower confidence limit
Output lower confidence limit for
structural predicted values
Output predicted values
Output predicted values of structural part
Output residuals
Output residuals from structural
predictions
Specify the name of a variable to contain
the part of the predictive error variance (
)
Specify the name of a variable to contain
recursive residuals
Output transformed variables
Output upper confidence limit
Output upper confidence limit for
structural predicted values
OUTPUT
CUSUMSQUB=
OUTPUT
CUSUMSQLB=
OUTPUT
LCL=
OUTPUT
LCLM=
OUTPUT
OUTPUT
OUTPUT
P=
PM=
R=
OUTPUT
RM=
OUTPUT
RECPEV=
OUTPUT
RECRES=
OUTPUT
OUTPUT
TRANSFORM=
UCL=
OUTPUT
UCLM=