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थीटा विधि×साधारण न्यूनतम वर्ग (OLS) समाश्रयण×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष20002019
प्रवर्तकAssimakopoulos & NikolopoulosWooldridge (textbook treatment); classical least squares
प्रकारUnivariate time-series forecasting modelLinear regression
मौलिक स्रोतAssimakopoulos, V. & Nikolopoulos, K. (2000). The Theta Model: A Decomposition Approach to Forecasting. International Journal of Forecasting, 16(4), 521-530. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
उपनामtheta model, theta forecasting, Theta Yöntemi — M3 Tahmin Yarışması Birincisiordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
संबंधित45
सारांशThe 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.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).
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