Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест Вальда-Вольфовица на число серий (runs test)× | Критерий Q Льюнга-Бокса для автокорреляции× | |
|---|---|---|
| Область≠ | Статистика | Эконометрика |
| Семейство | Hypothesis test | Hypothesis test |
| Год появления≠ | 1940 | 1978 |
| Автор метода≠ | Abraham Wald & Jacob Wolfowitz | Greta Ljung & George Box |
| Тип≠ | Nonparametric randomness test | Portmanteau goodness-of-fit test |
| Основополагающий источник≠ | Wald, A. & Wolfowitz, J. (1940). On a test whether two samples are from the same population. Annals of Mathematical Statistics, 11(2), 147–162. DOI ↗ | 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 ↗ |
| Другие названия≠ | Wald-Wolfowitz test, runs test for randomness, Runs Testi (Wald-Wolfowitz) | Ljung-Box Q Test, Modified Box-Pierce Test, Portmanteau Test for Autocorrelation, Otokorelasyon Portmanteau Testi |
| Связанные≠ | 5 | 3 |
| Сводка≠ | The Wald-Wolfowitz runs test is a nonparametric hypothesis test that determines whether a sequence of observations — coded as a series of binary symbols — follows a random pattern or contains systematic structure. Introduced by Abraham Wald and Jacob Wolfowitz in 1940, the test counts the number of uninterrupted runs of identical symbols and asks whether that count is consistent with random arrangement. | 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. |
| ScholarGateНабор данных ↗ |
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