เปรียบเทียบวิธี

	Fourier OLS (Fourier-Augmented Ordinary Least Squares)	การถดถอยกำลังสองน้อยที่สุดสามัญ (OLS)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2004	2019
ผู้ริเริ่ม	Becker, Enders, and Hurn	Wooldridge (textbook treatment); classical least squares
ประเภท	Augmented linear regression	Linear regression
แหล่งต้นตำรับ	Becker, R., Enders, W., & Hurn, S. (2004). A general test for time dependence in parameters. Journal of Applied Econometrics, 19(7), 899–906.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
ชื่อเรียกอื่น	Fourier OLS, Fourier-augmented OLS, trigonometric OLS, smooth structural break OLS	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
ที่เกี่ยวข้อง	6	5
สรุป	Fourier OLS is an OLS regression extended by adding low-frequency trigonometric (sine and cosine) terms to the regressor matrix. These Fourier components approximate smooth, gradual structural changes in the regression relationship over time without requiring knowledge of the number, timing, or form of the breaks.	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).