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Mfumo wa ARIMA (Autoregressive Integrated Moving Average)×Kipimo cha Breusch-Godfrey LM cha Uhusiano wa Mfuatano×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili20151978
MwanzilishiBox & Jenkins (Box-Jenkins methodology)Trevor Breusch & Leslie Godfrey
AinaUnivariate time-series modelLagrange-multiplier test for serial correlation
Chanzo asiliaBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Godfrey, L. G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46(6), 1293–1301. DOI ↗
Majina mbadalaBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliBG test, LM test for autocorrelation, Breusch-Godfrey serial correlation test, Breusch-Godfrey otokorelasyon testi
Zinazohusiana53
MuhtasariARIMA 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).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.
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ScholarGateLinganisha mbinu: ARIMA · Breusch-Godfrey Test. Imepatikana 2026-06-20 kutoka https://scholargate.app/sw/compare