পদ্ধতির তুলনা করুন

	সাধারণ ন্যূনতম বর্গক্ষেত্র (OLS) রিগ্রেশন	মসৃণ রূপান্তর স্বয়ংক্রীয় রিগ্রেশন (STAR) মডেল
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	2019	1994
প্রবর্তক	Wooldridge (textbook treatment); classical least squares	Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
ধরন	Linear regression	Nonlinear time-series regime-switching model
মৌলিক উৎস	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218.
অপর নাম	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
সম্পর্কিত	5	4
সারসংক্ষেপ	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 Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations.