Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест Бай-Перрона на множественные структурные сдвиги× | Модель SARIMA× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство≠ | Hypothesis test | Regression model |
| Год появления≠ | 1998 | 1970 (first edition); 1976 (revised) |
| Автор метода≠ | Jushan Bai & Pierre Perron | Box, Jenkins, and Reinsel |
| Тип≠ | Sequential hypothesis test for multiple structural breaks | Seasonal time series model |
| Основополагающий источник≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 |
| Другие названия | Bai-Perron Multiple Break Test, Multiple Structural Change Test, Sequential Structural Break Test, Çoklu Yapısal Kırılma Testi | SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component |
| Связанные≠ | 2 | 5 |
| Сводка≠ | The Bai-Perron test, introduced by Jushan Bai and Pierre Perron in their landmark 1998 Econometrica paper, is a least-squares-based procedure for detecting, estimating, and testing the number of structural breaks in a linear regression model estimated on time-series data. Unlike single-break tests, it simultaneously identifies multiple change-points in a sample, providing economists and empirical researchers with a rigorous, data-driven way to locate parameter instability across time. | SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics. |
| ScholarGateНабор данных ↗ |
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