Võrdle meetodeid

	Ljung-Boksi Q-test autokorrelatsiooni tuvastamiseks	ARIMA (autoregressiivne integreeritud liikuv keskmine) mudel
Valdkond	Ökonomeetria	Ökonomeetria
Perekond	Hypothesis test	Regression model
Tekkeaasta	1978	2015
Looja	Greta Ljung & George Box	Box & Jenkins (Box-Jenkins methodology)
Tüüp	Portmanteau goodness-of-fit test	Univariate time-series model
Algallikas	Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297–303.	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
Rööpnimetused	Ljung-Box Q Test, Modified Box-Pierce Test, Portmanteau Test for Autocorrelation, Otokorelasyon Portmanteau Testi	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Seotud	3	5
Kokkuvõte	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.	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).