Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель ARIMA (авторегрессионная интегрированная скользящая средняя)× | Бутстреп-вывод× | |
|---|---|---|
| Область≠ | Эконометрика | Статистика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2015 | 1979 |
| Автор метода≠ | Box & Jenkins (Box-Jenkins methodology) | Bradley Efron |
| Тип≠ | Univariate time-series model | Resampling-based inference |
| Основополагающий источник≠ | 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 | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ |
| Другие названия≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı |
| Связанные | 5 | 5 |
| Сводка≠ | 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). | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. |
| ScholarGateНабор данных ↗ |
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