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| Тест на Бройш-Годфри (LM) за автокорелация× | Модел ARIMA (Autoregressive Integrated Moving Average)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1978 | 2015 |
| Създател≠ | Trevor Breusch & Leslie Godfrey | Box & Jenkins (Box-Jenkins methodology) |
| Тип≠ | Lagrange-multiplier test for serial correlation | Univariate time-series model |
| Основополагащ източник≠ | Godfrey, L. G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46(6), 1293–1301. 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≠ | BG test, LM test for autocorrelation, Breusch-Godfrey serial correlation test, Breusch-Godfrey otokorelasyon testi | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| Свързани≠ | 3 | 5 |
| Резюме≠ | The Breusch-Godfrey test is a Lagrange-multiplier test for serial correlation in regression residuals, developed independently by Trevor Breusch (1978) and Leslie Godfrey (1978). Unlike the Durbin-Watson test, it detects autocorrelation up to any chosen order p, remains valid when the model includes lagged dependent variables, and produces a definite chi-square p-value rather than an inconclusive region — making it the modern standard for autocorrelation testing. | 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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