Sammenlign metoder
Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.
| Autoregressiv model (AR)× | ARMA-model (Autoregressiv glidende gennemsnit)× | |
|---|---|---|
| Fagområde | Økonometri | Økonometri |
| Familie | Regression model | Regression model |
| Oprindelsesår≠ | 1970s (popularised 1976) | 1970 |
| Ophavsperson | George E. P. Box and Gwilym M. Jenkins | George E. P. Box and Gwilym M. Jenkins |
| Type | Time series model | Time series model |
| Oprindelig kilde≠ | Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043 | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| Aliasser | AR model, AR(p) model, autoregression, AR process | ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q) |
| Relaterede≠ | 6 | 5 |
| Resumé≠ | 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. | 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. |
| ScholarGateDatasæt ↗ |
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