Sammenlign metoder
Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.
| ARIMA (Autoregressive Integrated Moving Average) Model× | KPSS-stationaritetstest× | |
|---|---|---|
| Fagområde | Økonometri | Økonometri |
| Familie | Regression model | Regression model |
| Oprindelsesår≠ | 2015 | 1992 |
| Ophavsperson≠ | Box & Jenkins (Box-Jenkins methodology) | Kwiatkowski, Phillips, Schmidt & Shin |
| Type≠ | Univariate time-series model | Stationarity test (reverse of unit-root tests) |
| Oprindelig kilde≠ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root. Journal of Econometrics, 54(1–3), 159–178. DOI ↗ |
| Aliasser | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | Kwiatkowski-Phillips-Schmidt-Shin test, stationarity test, KPSS durağanlık testi |
| Relaterede≠ | 5 | 4 |
| Resumé≠ | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | The KPSS test, introduced by Kwiatkowski, Phillips, Schmidt and Shin in 1992, tests the null hypothesis that a series is stationary against the alternative that it contains a unit root — the reverse of the ADF and Phillips-Perron tests. By flipping the burden of proof, it is designed to be used alongside unit-root tests so that the two can confirm one another and expose ambiguous, borderline cases. |
| ScholarGateDatasæt ↗ |
|
|