By Ingegerd Skoglund.
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Additional resources for Algorithms for a partially regularized least squares problem
Semiparametric approaches to flownormalisation and source apportionment of substances transport in rivers. Environmetrics, 12:233–250, 2001.
Silverman. Nonparametric regression and generalized linear models - a roughness penalty approach. Chapman & Hill, London, 1994. C. Hansen. Rank-Deficient and Discrete Ill-Posed Problems. Numerical Aspects of Linear Inversion. SIAM, Philadelphia, 1998. R. Hestenes and E. Stiefel. Methods of conjugate gradients for solving linear stystem. Journal of Research of the National Bureau of Standards, B49:409–436, 1952. H. Reinsch. Smoothing by spline functions. 10:177–183, 1967. Numerische Mathematik, 19 “lic” — 2007/4/23 — 11:29 — page 20 — #32  P.
A. Girard. A fast ’Monte-Carlo cross-validation’ procedure for large least squares problems with noisy data. Numerische Mathematik, 56:1–23, 1989. H. T. Heath and G. Wahba. Generalized cross-validation as a method for choosing a good ridge parameter. Technometrics, 21:215–223, 1979. H. F. Van Loan. Matrix Computaions. , Johns Hopkins University Press, Baltimore, 1996. J. W. Silverman. Nonparametric regression and generalized linear models - a roughness penalty approach. Chapman & Hill, London, 1994.
Algorithms for a partially regularized least squares problem by Ingegerd Skoglund.