手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| Phillips-Perron (PP) 単位根検定× | ARIMA（自己回帰和分移動平均）モデル× | |
|---|---|---|
| 分野 | 計量経済学 | 計量経済学 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1988 | 2015 |
| 提唱者≠ | Peter C. B. Phillips & Pierre Perron | Box & Jenkins (Box-Jenkins methodology) |
| 種類≠ | Unit-root test for stationarity | Univariate time-series model |
| 原典≠ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ | 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 |
| 別名 | PP test, Phillips-Perron unit root test, Phillips-Perron birim kök testi | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| 関連≠ | 4 | 5 |
| 概要≠ | The Phillips-Perron test, proposed by Peter Phillips and Pierre Perron in 1988, tests for a unit root in a time series, like the Augmented Dickey-Fuller test, but corrects for autocorrelation and heteroskedasticity in the errors non-parametrically rather than by adding lagged differences. It runs a simple Dickey-Fuller regression and then adjusts the test statistic using a long-run variance estimate, so the practitioner need not choose a lag length for the regression itself. | 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). |
| ScholarGateデータセット ↗ |
|
|