เปรียบเทียบวิธี

	Prophet	การถดถอยกำลังสองน้อยที่สุดสามัญ (OLS)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2018	2019
ผู้ริเริ่ม	Taylor & Letham (Facebook/Meta)	Wooldridge (textbook treatment); classical least squares
ประเภท	Decomposable (structural) time series model	Linear regression
แหล่งต้นตำรับ	Taylor, S. J. & Letham, B. (2018). Forecasting at Scale. The American Statistician, 72(1), 37-45.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
ชื่อเรียกอื่น	Prophet, Facebook Prophet, Meta Prophet, forecasting at scale	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
ที่เกี่ยวข้อง	5	5
สรุป	Prophet is a Bayesian structural time series model introduced by Taylor and Letham at Facebook/Meta in 2018. It forecasts a continuous series by decomposing it into separate, interpretable trend, seasonality, and holiday components, and is designed to be approachable for analysts working at scale.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).