The ARIMA Procedure
- Overview
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Getting Started
The Three Stages of ARIMA Modeling Identification Stage Estimation and Diagnostic Checking Stage Forecasting Stage Using ARIMA Procedure Statements General Notation for ARIMA Models Stationarity Differencing Subset, Seasonal, and Factored ARMA Models Input Variables and Regression with ARMA Errors Intervention Models and Interrupted Time Series Rational Transfer Functions and Distributed Lag Models Forecasting with Input Variables Data Requirements -
Syntax
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Details
The Inverse Autocorrelation Function The Partial Autocorrelation Function The Cross-Correlation Function The ESACF Method The MINIC Method The SCAN Method Stationarity Tests Prewhitening Identifying Transfer Function Models Missing Values and Autocorrelations Estimation Details Specifying Inputs and Transfer Functions Initial Values Stationarity and Invertibility Naming of Model Parameters Missing Values and Estimation and Forecasting Forecasting Details Forecasting Log Transformed Data Specifying Series Periodicity Detecting Outliers OUT= Data Set OUTCOV= Data Set OUTEST= Data Set OUTMODEL= SAS Data Set OUTSTAT= Data Set Printed Output ODS Table Names Statistical Graphics
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Examples
- References
| ODS Table Names |
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.
ODS Table Name |
Description |
Statement |
Option |
|---|---|---|---|
ChiSqAuto |
chi-square statistics table for autocorrelation |
IDENTIFY |
|
ChiSqCross |
chi-square statistics table for cross-correlations |
IDENTIFY |
CROSSCORR |
CorrGraph |
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 |