The ARIMA Procedure
- Overview
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Getting Started
The Three Stages of ARIMA ModelingIdentification StageEstimation and Diagnostic Checking StageForecasting StageUsing ARIMA Procedure StatementsGeneral Notation for ARIMA ModelsStationarityDifferencingSubset, Seasonal, and Factored ARMA ModelsInput Variables and Regression with ARMA ErrorsIntervention Models and Interrupted Time SeriesRational Transfer Functions and Distributed Lag ModelsForecasting with Input VariablesData Requirements -
Syntax
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DetailsThe Inverse Autocorrelation FunctionThe Partial Autocorrelation FunctionThe Cross-Correlation FunctionThe ESACF MethodThe MINIC MethodThe SCAN MethodStationarity TestsPrewhiteningIdentifying Transfer Function ModelsMissing Values and AutocorrelationsEstimation DetailsSpecifying Inputs and Transfer FunctionsInitial ValuesStationarity and InvertibilityNaming of Model ParametersMissing Values and Estimation and ForecastingForecasting DetailsForecasting Log Transformed DataSpecifying Series PeriodicityDetecting OutliersOUT= Data SetOUTCOV= Data SetOUTEST= Data SetOUTMODEL= SAS Data SetOUTSTAT= Data SetPrinted OutputODS Table NamesStatistical Graphics
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Examples
- References
PROC ARIMA assigns a name to each table it creates. You can use these names to reference the table when you use the Output Delivery System (ODS) to select tables and create output data sets. These names are listed in Table 7.12.
Table 7.12: ODS Tables Produced by PROC ARIMA
|
ODS Table Name |
Description |
Statement |
Option |
|---|---|---|---|
|
ChiSqAuto |
chi-square statistics table for autocorrelation |
IDENTIFY |
|
|
ChiSqCross |
chi-square statistics table for cross-correlations |
IDENTIFY |
CROSSCORR |
|
AutoCorrGraph |
Correlations graph |
IDENTIFY |
|
|
CrossCorrGraph |
Cross-Correlations graph |
IDENTIFY |
|
|
DescStats |
Descriptive statistics |
IDENTIFY |
|
|
ESACF |
Extended sample autocorrelation function |
IDENTIFY |
ESACF |
|
ESACFPValues |
ESACF probability values |
IDENTIFY |
ESACF |
|
IACFGraph |
Inverse autocorrelations graph |
IDENTIFY |
|
|
InputDescStats |
Input descriptive statistics |
IDENTIFY |
|
|
MINIC |
Minimum information criterion |
IDENTIFY |
MINIC |
|
PACFGraph |
Partial autocorrelations graph |
IDENTIFY |
|
|
SCAN |
Squared canonical correlation estimates |
IDENTIFY |
SCAN |
|
SCANPValues |
SCAN chi-square probability values |
IDENTIFY |
SCAN |
|
StationarityTests |
Stationarity tests |
IDENTIFY |
STATIONARITY |
|
TentativeOrders |
Tentative order selection |
IDENTIFY |
MINIC, ESACF, or SCAN |
|
ARPolynomial |
Filter equations |
ESTIMATE |
|
|
ChiSqAuto |
chi-square statistics table for autocorrelation |
ESTIMATE |
|
|
ChiSqCross |
chi-square statistics table for cross-correlations |
ESTIMATE |
|
|
CorrB |
Correlations of the estimates |
ESTIMATE |
|
|
DenPolynomial |
Filter equations |
ESTIMATE |
|
|
FitStatistics |
Fit statistics |
ESTIMATE |
|
|
IterHistory |
Iteration history |
ESTIMATE |
PRINTALL |
|
InitialAREstimates |
Initial autoregressive parameter estimates |
ESTIMATE |
|
|
InitialMAEstimates |
Initial moving-average parameter estimates |
ESTIMATE |
|
|
InputDescription |
Input description |
ESTIMATE |
|
|
MAPolynomial |
Filter equations |
ESTIMATE |
|
|
ModelDescription |
Model description |
ESTIMATE |
|
|
NumPolynomial |
Filter equations |
ESTIMATE |
|
|
ParameterEstimates |
Parameter estimates |
ESTIMATE |
|
|
PrelimEstimates |
Preliminary estimates |
ESTIMATE |
|
|
ObjectiveGrid |
Objective function grid matrix |
ESTIMATE |
GRID |
|
OptSummary |
ARIMA estimation optimization |
ESTIMATE |
PRINTALL |
|
OutlierDetails |
Detected outliers |
OUTLIER |
|
|
Forecasts |
Forecast |
FORECAST |