قارن الطرق

	نموذج ARIMA (الانحدار الذاتي المتكامل المتوسط المتحرك)	اختبار باي-بيرون لتعدد نقاط التغير الهيكلي
المجال	الاقتصاد القياسي	الاقتصاد القياسي
العائلة	Regression model	Hypothesis test
سنة النشأة	1970	1998
صاحب الطريقة	George Box and Gwilym Jenkins	Jushan Bai & Pierre Perron
النوع	Time series forecasting model	Sequential hypothesis test for multiple structural breaks
المصدر التأسيسي	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.
الأسماء البديلة	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)	Bai-Perron Multiple Break Test, Multiple Structural Change Test, Sequential Structural Break Test, Çoklu Yapısal Kırılma Testi
ذات صلة	6	2
الملخص	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 Bai-Perron test, introduced by Jushan Bai and Pierre Perron in their landmark 1998 Econometrica paper, is a least-squares-based procedure for detecting, estimating, and testing the number of structural breaks in a linear regression model estimated on time-series data. Unlike single-break tests, it simultaneously identifies multiple change-points in a sample, providing economists and empirical researchers with a rigorous, data-driven way to locate parameter instability across time.