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Model ARIMA (Autoregressive Integrated Moving Average)×Uji Diebold-Mariano untuk Akurasi Prediktif yang Sama×
BidangEkonometrikaEkonometrika
KeluargaRegression modelHypothesis test
Tahun asal20151995
PencetusBox & Jenkins (Box-Jenkins methodology)Francis Diebold & Roberto Mariano
TipeUnivariate time-series modelNon-parametric forecast comparison test
Sumber perintisBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗
AliasBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliDM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi
Terkait53
RingkasanARIMA 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 Diebold-Mariano (DM) test, introduced by Diebold and Mariano in 1995, is a widely used non-parametric procedure for formally comparing the predictive accuracy of two competing forecasting models. It evaluates whether the difference in forecast errors between two models is statistically significant, without requiring nested models or specific distributional assumptions about the forecasts, making it broadly applicable across economics, finance, and time-series analysis.
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ScholarGateBandingkan metode: ARIMA · Diebold-Mariano Test. Diakses 2026-06-19 dari https://scholargate.app/id/compare