These functions calculates the solution for the generalized and/or mixed total least squares problem.
The total least squares problem, also known as errors in variables, solves the over-determined set of linear equations (A0+dA)X = (B0+dB), where covariance matrix of the unknown disturbances dA and dB is considered to be diagonal and denoted by E([dA dB]^T[dA dB]) = sigma_d.*I.
The mixed total least squares problem solves the over-determined set of linear equations [A1 A2]X = B, where A1 are the error-free variables, and A2 = A0 + dA2 and B = B0 + dB are the variables with disturbances.
The generalized total least squares problem solves the over-determined set of linear equations (A0 + dA)X = (B0 + dB), where the covariance matrix of the disturbances dA and dB is positive definite and given by sigma_d.*W = E([dA dB]^T[dA dB]).
Ivo Houtzager (2022). Total Least Squares with mixed and/or weighted disturbances (https://github.com/iwoodsawyer/gtls/releases/tag/v184.108.40.206), GitHub. Retrieved .
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Inspired by: QR/RQ/QL/LQ factorizations
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