%A Majumdar, Rajeshwari
%D 2018
%T On Least Squares Linear Regression Without Second Moment
%K
%X If X and Y are real valued random variables such that the first moments of X , Y , and XY exist and the conditional expectation of Y given X is an affine function of X , then the intercept and slope of the conditional expectation equal the intercept and slope of the least squares linear regression function, even though Y may not have a finite second moment. As a consequence, the affine in X form of the conditional expectation and zero covariance imply mean independence.
%U https://mjum.math.umn.edu/index.php/mjum/article/view/72
%J Minnesota Journal of Undergraduate Mathematics
%0 Journal Article
%V 4
%N 1
%@ 2378-5810
%8 2018-06-25