Linganisha mbinu

	Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)	Njia ya Theta
Nyanja	Ekonometriki	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	2019	2000
Mwanzilishi	Wooldridge (textbook treatment); classical least squares	Assimakopoulos & Nikolopoulos
Aina	Linear regression	Univariate time-series forecasting model
Chanzo asilia	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Assimakopoulos, V. & Nikolopoulos, K. (2000). The Theta Model: A Decomposition Approach to Forecasting. International Journal of Forecasting, 16(4), 521-530.
Majina mbadala	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	theta model, theta forecasting, Theta Yöntemi — M3 Tahmin Yarışması Birincisi
Zinazohusiana	5	4
Muhtasari	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).	The Theta Method is a univariate time-series forecasting model introduced by Assimakopoulos and Nikolopoulos in 2000. It decomposes a series into two theta lines that capture its long-run trend and its short-run dynamics, forecasts each line separately, and combines them by a weighted average. Its simplicity and accuracy made it the winner of the M3 forecasting competition.