পদ্ধতির তুলনা করুন

	ব্রেউশ-গডফ্রে এলএম টেস্ট ফর সিরিয়াল কোরিলেশন	ARIMA (Autoregressive Integrated Moving Average) মডেল
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1978	2015
প্রবর্তক	Trevor Breusch & Leslie Godfrey	Box & Jenkins (Box-Jenkins methodology)
ধরন	Lagrange-multiplier test for serial correlation	Univariate time-series model
মৌলিক উৎস	Godfrey, L. G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46(6), 1293–1301.	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
অপর নাম	BG test, LM test for autocorrelation, Breusch-Godfrey serial correlation test, Breusch-Godfrey otokorelasyon testi	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
সম্পর্কিত	3	5
সারসংক্ষেপ	The Breusch-Godfrey test is a Lagrange-multiplier test for serial correlation in regression residuals, developed independently by Trevor Breusch (1978) and Leslie Godfrey (1978). Unlike the Durbin-Watson test, it detects autocorrelation up to any chosen order p, remains valid when the model includes lagged dependent variables, and produces a definite chi-square p-value rather than an inconclusive region — making it the modern standard for autocorrelation testing.	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).