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
Subsections:
- 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