Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de Media Móvil (MA)× | Modelo ARMA (Autoregresivo de Media Móvil)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen | 1970 | 1970 |
| Autor original≠ | Box and Jenkins | George E. P. Box and Gwilym M. Jenkins |
| Tipo≠ | Linear time series model | Time series model |
| Fuente seminal≠ | 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. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| Alias | MA model, MA(q) process, moving-average process, Box-Jenkins MA | ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q) |
| Relacionados | 5 | 5 |
| Resumen≠ | 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. | The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting. |
| ScholarGateConjunto de datos ↗ |
|
|