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	बेयसियन एरिमा मॉडल	ऑटोरेग्रेसिव इंटीग्रेटेड मूविंग एवरेज (ARIMA) मॉडल
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1970s (ARIMA); Bayesian extension prominent from 1990s	1970
प्रवर्तक	Pole, West & Harrison (Bayesian treatment); Box & Jenkins (ARIMA foundation)	George Box and Gwilym Jenkins
प्रकार	Bayesian time series model	Time series forecasting model
मौलिक स्रोत	Pole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
उपनाम	Bayesian ARIMA, BARIMA, Bayesian Box-Jenkins model, Bayesian integrated time series model	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
संबंधित	6	6
सारांश	The Bayesian ARIMA model combines the classical Box-Jenkins ARIMA framework with Bayesian inference. Instead of obtaining single point estimates for autoregressive and moving average parameters, it places prior distributions over them and uses observed data to update beliefs into a full posterior distribution, enabling coherent uncertainty quantification and probabilistic forecasting.	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.