bigsplines (1.1-1)

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Smoothing Splines for Large Samples.

Fits smoothing spline regression models using scalable algorithms designed for large samples. Seven marginal spline types are supported: linear, cubic, different cubic, cubic periodic, cubic thin-plate, ordinal, and nominal. Random effects and parametric effects are also supported. Response can be Gaussian or non-Gaussian: Binomial, Poisson, Gamma, Inverse Gaussian, or Negative Binomial.

Maintainer: Nathaniel E. Helwig
Author(s): Nathaniel E. Helwig <>

License: GPL (>= 2)

Uses: quadprog
Reverse depends: eegkit

Released about 1 year ago.

7 previous versions



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