Ehud Altman, Kenneth R. Brown, et al.
PRX Quantum
A new principle of least-squares estimation is described, which extends the old in allowing the estimation of the number of the parameters along with their values. Just as the old principle, the new one too uses only a sum of squares, which now, however, represent prediction errors rather than fitting errors. In a typical regression problem with independent normal data, the estimates of the number of the parameters, i.e. the number of the regressor functions, are shown to be consistent. © 1986 Oxford University Press.
Ehud Altman, Kenneth R. Brown, et al.
PRX Quantum
Hang-Yip Liu, Steffen Schulze, et al.
Proceedings of SPIE - The International Society for Optical Engineering
R.A. Brualdi, A.J. Hoffman
Linear Algebra and Its Applications
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence