On algorithms for ordinary least squares regression spline fitting: A comparative study

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Parameter estimation of ODE’s via nonparametric estimators (2007, methodology): “As in [15, 27], we use d(Km) = 3m + 1, and we use an heuristic for considering efficiently the various subsets, which is based on the elimination of the less informative knots (for GCV), and the addition of the more informative knots in order to minimize the GCV criterion (ElimAdd procedure in [27])”
Knot selection for least-squares and penalized splines (2013, methodology): “Rather than the discretization approach used by Pitman and Murthy [11] and Pitman [12] and Lee [13,14], we treat the knot locations as continuous variables.”