Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель ARIMA (авторегрессионная интегрированная скользящая средняя)× | Тест Чау на структурный сдвиг× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1970 | 1960 |
| Автор метода≠ | George Box and Gwilym Jenkins | Gregory C. Chow |
| Тип≠ | Time series forecasting model | Test for structural break in regression coefficients |
| Основополагающий источник≠ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ | Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605. DOI ↗ |
| Другие названия≠ | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) | Chow breakpoint test, structural break test, Chow yapısal kırılma testi |
| Связанные≠ | 6 | 2 |
| Сводка≠ | The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics. | The Chow test, introduced by Gregory Chow in 1960, checks whether the coefficients of a linear regression are the same across two subsamples — that is, whether a structural break occurs at a known point such as a policy change, crisis, or regime shift. It compares the fit of a single pooled regression with the combined fit of two separate regressions; a large improvement from splitting indicates the relationship differs between the two periods or groups. |
| ScholarGateНабор данных ↗ |
|
|