เปรียบเทียบวิธี

	แบบจำลอง Autoregressive (AR) แบบเบย์ (Bayesian AR Model)	แบบจำลองออโตเรเกรสซีฟ (AR)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1971	1970s (popularised 1976)
ผู้ริเริ่ม	Arnold Zellner; foundational Bayesian time-series work by West & Harrison	George E. P. Box and Gwilym M. Jenkins
ประเภท	Bayesian time-series model	Time series model
แหล่งต้นตำรับ	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376	Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043
ชื่อเรียกอื่น	Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression	AR model, AR(p) model, autoregression, AR process
ที่เกี่ยวข้อง	6	6
สรุป	The Bayesian AR model estimates an autoregressive time-series process by combining a likelihood derived from the AR structure with prior distributions over the lag coefficients and error variance. Rather than producing single point estimates, it yields full posterior distributions, enabling principled uncertainty quantification and probabilistic forecasting.	An autoregressive model of order p — AR(p) — expresses the current value of a time series as a linear function of its own p most recent past values plus a white-noise error. It is the building block of the Box-Jenkins family of time-series models and is widely used for forecasting stationary economic and financial series.