R package bigsplines. Fits smoothing spline regression models using scalable algorithms designed for large samples. Six marginal spline types are supported: 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.

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  1. Helwig, Nathaniel E.: Efficient estimation of variance components in nonparametric mixed-effects models with large samples (2016)