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| Тест на Лиунг-Бокс Q за автокорелация× | Модел ARIMA (Autoregressive Integrated Moving Average)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство≠ | Hypothesis test | Regression model |
| Година на възникване≠ | 1978 | 2015 |
| Създател≠ | Greta Ljung & George Box | Box & Jenkins (Box-Jenkins methodology) |
| Тип≠ | Portmanteau goodness-of-fit test | Univariate time-series model |
| Основополагащ източник≠ | Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297–303. 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 |
| Други названия≠ | Ljung-Box Q Test, Modified Box-Pierce Test, Portmanteau Test for Autocorrelation, Otokorelasyon Portmanteau Testi | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| Свързани≠ | 3 | 5 |
| Резюме≠ | The Ljung-Box Q test is a diagnostic portmanteau test proposed by Ljung and Box (1978) to assess whether a group of autocorrelations in a time series residual sequence is jointly zero. It is widely used to evaluate the adequacy of fitted time series models — especially ARIMA models — by testing whether remaining residuals exhibit any systematic pattern. The test is applicable in econometrics, finance, and any field that relies on temporal data modeling. | 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). |
| ScholarGateНабор от данни ↗ |
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