Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Μοντέλο Κινητού Μέσου Όρου (MA)× | Αυτοπαλινδρομικό Μοντέλο (AR)× | |
|---|---|---|
| Πεδίο | Οικονομετρία | Οικονομετρία |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 1970 | 1970s (popularised 1976) |
| Δημιουργός≠ | Box and Jenkins | George E. P. Box and Gwilym M. Jenkins |
| Τύπος≠ | Linear time series model | Time series model |
| Θεμελιώδης πηγή≠ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 | Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043 |
| Εναλλακτικές ονομασίες | MA model, MA(q) process, moving-average process, Box-Jenkins MA | AR model, AR(p) model, autoregression, AR process |
| Συναφείς≠ | 5 | 6 |
| Σύνοψη≠ | The Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods. | An autoregressive model of order p — AR(p) — expresses the current value of a time series as a linear function of its own p most recent past values plus a white-noise error. It is the building block of the Box-Jenkins family of time-series models and is widely used for forecasting stationary economic and financial series. |
| ScholarGateΣύνολο δεδομένων ↗ |
|
|