Autoregressive Integrated Moving Average models
GPTKB entity
Statements (40)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
statistical analysis
|
| gptkbp:abbreviation |
gptkb:ARIMA
|
| gptkbp:appliesTo |
gptkb:signal_processing
finance weather forecasting econometrics |
| gptkbp:assumes |
linearity
normality of errors no autocorrelation in residuals |
| gptkbp:component |
autoregressive (AR)
integrated (I) moving average (MA) |
| gptkbp:generalizes |
autoregressive models
ARMA models moving average models |
| https://www.w3.org/2000/01/rdf-schema#label |
Autoregressive Integrated Moving Average models
|
| gptkbp:implementedIn |
gptkb:Python
gptkb:SAS gptkb:MATLAB R |
| gptkbp:introduced |
Box and Jenkins
|
| gptkbp:introducedIn |
1970
|
| gptkbp:limitation |
sensitive to outliers
not suitable for non-linear time series requires stationary data (after differencing) |
| gptkbp:mathematical_form |
ARIMA(p,d,q)
|
| gptkbp:parameter |
q
p d |
| gptkbp:relatedTo |
gptkb:SARIMA
gptkb:ARIMAX gptkb:Box–Jenkins_methodology |
| gptkbp:requires |
parameter estimation
diagnostic checking model identification stationarity (after differencing) |
| gptkbp:usedFor |
time series analysis
forecasting |
| gptkbp:bfsParent |
gptkb:ARIMA_models
|
| gptkbp:bfsLayer |
7
|