পদ্ধতির তুলনা করুন

	অরৈখিক ওএলএস (অরৈখিক ক্ষুদ্রতম বর্গ)	সাধারণ ন্যূনতম বর্গক্ষেত্র (OLS) রিগ্রেশন
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1974–1987	2019
প্রবর্তক	Gallant (1987); Wooldridge (2010) for econometric treatment	Wooldridge (textbook treatment); classical least squares
ধরন	Nonlinear regression estimator	Linear regression
মৌলিক উৎস	Gallant, A. R. (1987). Nonlinear Statistical Models. John Wiley & Sons. ISBN: 978-0471802600	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
অপর নাম	nonlinear least squares, NLS, NLLS, nonlinear regression	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
সম্পর্কিত	5	5
সারসংক্ষেপ	Nonlinear Ordinary Least Squares (NLS) estimates regression models in which the conditional mean function is nonlinear in the parameters. Like standard OLS it minimises the sum of squared residuals, but because no closed-form solution exists the estimator is found by iterative numerical optimisation. Under standard regularity conditions NLS is consistent and asymptotically normal.	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).