선형 회귀 (Korean Wikipedia)

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del Pino, Guido (1989). “The Unifying Role of Iterative Generalized Least Squares in Statistical Algorithms”. 《Statistical Science》 4 (4): 394–403. doi:10.1214/ss/1177012408. JSTOR 2245853.
Cohen, Michael; Dalal, Siddhartha R.; Tukey,John W. (1993). “Robust, Smoothly Heterogeneous Variance Regression”. 《Journal of the Royal Statistical Society, Series C》 42 (2): 339–353. JSTOR 2986237.
Stone, C. J. (1975). “Adaptive maximum likelihood estimators of a location parameter”. 《The Annals of Statistics》 3 (2): 267–284. doi:10.1214/aos/1176343056. JSTOR 2958945.
Deaton, Angus (1992). 《Understanding Consumption》. Oxford University Press. ISBN 0-19-828824-7.

Rencher, Alvin C.; Christensen, William F. (2012), 〈Chapter 10, Multivariate regression – Section 10.1, Introduction〉, 《Methods of Multivariate Analysis》, Wiley Series in Probability and Statistics 709 3판, John Wiley & Sons, 19쪽, ISBN 9781118391679
Yan, Xin (2009), 《Linear Regression Analysis: Theory and Computing》, World Scientific, 1–2쪽, ISBN 9789812834119, Regression analysis ... is probably one of the oldest topics in mathematical statistics dating back to about two hundred years ago. The earliest form of the linear regression was the least squares method, which was published by Legendre in 1805, and by Gauss in 1809 ... Legendre and Gauss both applied the method to the problem of determining, from astronomical observations, the orbits of bodies about the sun.

Tofallis, C (2009). “Least Squares Percentage Regression”. 《Journal of Modern Applied Statistical Methods》 7: 526–534. doi:10.2139/ssrn.1406472.
del Pino, Guido (1989). “The Unifying Role of Iterative Generalized Least Squares in Statistical Algorithms”. 《Statistical Science》 4 (4): 394–403. doi:10.1214/ss/1177012408. JSTOR 2245853.
Carroll, Raymond J. (1982). “Adapting for Heteroscedasticity in Linear Models”. 《The Annals of Statistics》 10 (4): 1224–1233. doi:10.1214/aos/1176345987. JSTOR 2240725.
Nievergelt, Yves (1994). “Total Least Squares: State-of-the-Art Regression in Numerical Analysis”. 《SIAM Review》 36 (2): 258–264. doi:10.1137/1036055. JSTOR 2132463.
Narula, Subhash C.; Wellington, John F. (1982). “The Minimum Sum of Absolute Errors Regression: A State of the Art Survey”. 《International Statistical Review》 50 (3): 317–326. doi:10.2307/1402501. JSTOR 1402501.
Stone, C. J. (1975). “Adaptive maximum likelihood estimators of a location parameter”. 《The Annals of Statistics》 3 (2): 267–284. doi:10.1214/aos/1176343056. JSTOR 2958945.

del Pino, Guido (1989). “The Unifying Role of Iterative Generalized Least Squares in Statistical Algorithms”. 《Statistical Science》 4 (4): 394–403. doi:10.1214/ss/1177012408. JSTOR 2245853.
Carroll, Raymond J. (1982). “Adapting for Heteroscedasticity in Linear Models”. 《The Annals of Statistics》 10 (4): 1224–1233. doi:10.1214/aos/1176345987. JSTOR 2240725.
Cohen, Michael; Dalal, Siddhartha R.; Tukey,John W. (1993). “Robust, Smoothly Heterogeneous Variance Regression”. 《Journal of the Royal Statistical Society, Series C》 42 (2): 339–353. JSTOR 2986237.
Nievergelt, Yves (1994). “Total Least Squares: State-of-the-Art Regression in Numerical Analysis”. 《SIAM Review》 36 (2): 258–264. doi:10.1137/1036055. JSTOR 2132463.
Narula, Subhash C.; Wellington, John F. (1982). “The Minimum Sum of Absolute Errors Regression: A State of the Art Survey”. 《International Statistical Review》 50 (3): 317–326. doi:10.2307/1402501. JSTOR 1402501.
Stone, C. J. (1975). “Adaptive maximum likelihood estimators of a location parameter”. 《The Annals of Statistics》 3 (2): 267–284. doi:10.1214/aos/1176343056. JSTOR 2958945.

Tofallis, C (2009). “Least Squares Percentage Regression”. 《Journal of Modern Applied Statistical Methods》 7: 526–534. doi:10.2139/ssrn.1406472.