Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Тест Вальда-Вольфовіца на кількість серій (runs test)× | Тест Люнга-Бокса Q для автокореляції× | |
|---|---|---|
| Галузь≠ | Статистика | Економетрика |
| Родина | Hypothesis test | Hypothesis test |
| Рік появи≠ | 1940 | 1978 |
| Автор методу≠ | Abraham Wald & Jacob Wolfowitz | Greta Ljung & George Box |
| Тип≠ | Nonparametric randomness test | Portmanteau goodness-of-fit test |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви≠ | 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 |
| Пов'язані≠ | 5 | 3 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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