JOPS | R Documentation |

A package for working with and learning about P-splines. P-splines combine B-splines with discrete penalties to build a very flexible and effective smooth models. They can handle non-normal data in the style of generalized linear models.

This package provides functions for constructing B-spline bases and penalty matrices. It solves the penalized likelihood equations efficiently.

Several methods are provided to determine the values of penalty parameters automatically, using cross-validation, AIC, mixed models or fast Bayesian algorithms.

This package is a companion to the book by Eilers and Marx (2021). The book presents the underlying theory and contains many examples and the code `R`

for each example is available on the website https://psplines.bitbucket.io

Eilers, P.H.C. and Marx, B.D. (2021). *Practical Smoothing, The Joys of
P-splines.* Cambridge University Press.

Eilers, P.H.C. and Marx, B.D. (1996). Flexible smoothing with
B-splines and penalties (with comments and rejoinder),
*Statistical Science*, 11: 89-121.

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