The orthogonal projection method and its regularized and statistical interpretation

Minimum distance estimators in regression and orthogonal projection estimators in conditional linear algebra are known to be useful for solving processing problems in multidimensional statistical analysis. A relationship between these estimators and regularized solutions of stochastic linear equations and a posteriori analogues of these equations is established.