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JOPS (version 0.2.0)

Practical Smoothing with P-Splines

Description

Functions and data to reproduce all plots in the book "Practical Smoothing. The Joys of P-splines" by Paul H.C. Eilers and Brian D. Marx (2021, ISBN:978-1108482950).

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Version

Install

install.packages('JOPS')

Monthly Downloads

346

Version

0.2.0

License

GPL-2 | GPL-3

Maintainer

Paul Eilers

Last Published

April 29th, 2025

Functions in JOPS (0.2.0)

Bayesian density estimation

Custom theme for ggplot

Translated number vector to bin index.

Fit asymmetry parameters in the expectile bundle model

Profile of a sanded piece of wood.

Brightness of a variable star.

Create a matrix of counts.

Deviance calculation for GLM P-spline fitting.

Fit amplitude coeffcients in the bundle model for expectiles

Smooth a 2D histogram

plot.ps2dsignal

Plotting function for ps2DSignal

Plotting function for ps2DGLM

plot.ps2dnormal

Plotting function for ps2DNormal

An X-ray diffractogram.

Inverse link function, used for GLM fitting.

Compute a 2D histogram

Fit a composite link model

Spinal bone relative mineral density

predict.pssignal

Predict function for psSignal

Compute a circular B-spline basis matrix

Plotting function for psSignal

Plotting function for sim_psr

Plotting function for sim_vcpsr

Ovarian cancer data

Plotting function for psNormal, psPoisson, psBinomial

predict.psvcsignal

Predict function for psVCSignal

Compute a second order circular differencing matrix

predict.ps2dglm

Predict function for ps2DGLM

Clone a B-spline basis for new x

plot.psvcsignal

Plotting function for psVCSignal

predict.ps2dsignal

Predict function for ps2DSignal

predict.ps2dnormal

Predict function for ps2DNormal

Derivative for a P-spline fit of scattered (normal) data.

predict.simvcpsr

Predict function for sim_vcpsr

Smoothing scattered Poisson data using P-splines.

Predict function for psNormal, psBinomial, psPoisson

Predict function for sim_psr

Smoothing scattered binomial data using P-splines.

Smoothing scattered (normal) data using P-splines.

Compute the row tensor product of two matrices

Save a plot as a PDF file.

Two-dimensional smoothing scattered (normal) data using P-splines.

Two-dimensional smoothing of scattered normal or non-normal (GLM) responses using tensor product P-splines.

Smooth signal (multivariate calibration) regression using P-splines.

Varying-coefficient penalized signal regression using P-splines.

Two-dimensional penalized signal regression using P-splines.

pspline2d_checker

P-spline 2D tensor product checking algorithm for the GLM.

ps2D_PartialDeriv

Partial derivative two-dimensional smoothing scattered (normal) data using P-splines.

Varying-coefficient single-index signal regression using tensor P-splines.

Single-Index signal regression using P-splines

Compute a truncated power function.

Prepare graphics layout for multiple panels

Open a graphics window.

Compute a sparse B-spline basis on evenly spaced knots

pspline_checker

P-spline checking algorithm for the GLM.

Observations on the widths of red blood cell distributions (RDW).

P-spline fitting algorithm for the GLM.

Chromosome G519C18 data

Custom color ramp.

Themeing functions used to unify ggplot features

Prices of hard disk drives

Joys of P-Splines

Two-dimensional P-spline smoothing

Simulation of CGH data

Prevalence of Hepatitis among a sample of Bulgarian males.

Deaths in Greece in 1960.

Sugar Processing Data

Environmental complaints from the Rijnomond area of The Netherlands

Compute a B-spline basis matrix

Suicide Data Set

A section of an ECG (electrocardiogram)