| bbase | Compute a B-spline basis matrix |
| binit | Translated number vector to bin index. |
| bone_data | Spinal bone relative mineral density |
| cbase | Compute a circular B-spline basis matrix |
| cdiff | Compute a second order circular differencing matrix |
| CGHsim | Simulation of CGH data |
| clone_base | Clone a B-spline basis for new x |
| Complaints | Environmental complaints from the Rijnomond area of The... |
| count2d | Create a matrix of counts. |
| dev_calc | Deviance calculation for GLM P-spline fitting. |
| Disks | Prices of hard disk drives |
| ECG | A section of an ECG (electrocardiogram) |
| fitampl | Fit amplitude coeffcients in the bundle model for expectiles |
| fitasy | Fit asymmetry parameters in the expectile bundle model |
| G519C18 | Chromosome G519C18 data |
| Greece_deaths | Deaths in Greece in 1960. |
| Hepatitis | Prevalence of Hepatitis among a sample of Bulgarian males. |
| hist2d | Compute a 2D histogram |
| hist2dsm | Smooth a 2D histogram |
| indiumoxide | An X-ray diffractogram. |
| inverse_link | Inverse link function, used for GLM fitting. |
| JOPS | Joys of P-Splines |
| JOPS_colors | Custom color ramp. |
| JOPS_point | Themeing functions used to unify ggplot features |
| JOPS_theme | Custom theme for ggplot |
| LAPS_dens | Bayesian density estimation |
| Mixture | Mixture Data |
| ova | Ovarian cancer data |
| pclm | Fit a composite link model |
| plot.ps2dglm | Plotting function for 'ps2DGLM' |
| plot.ps2dnormal | Plotting function for 'ps2DNormal' |
| plot.ps2dsignal | Plotting function for 'ps2DSignal' |
| plot.pspfit | Plotting function for 'psNormal', 'psPoisson', 'psBinomial' |
| plot.pssignal | Plotting function for 'psSignal' |
| plot.psvcsignal | Plotting function for 'psVCSignal' |
| plot.simpsr | Plotting function for 'sim_psr' |
| plot.simvcpsr | Plotting function for 'sim_vcpsr' |
| predict.ps2dglm | Predict function for 'ps2DGLM' |
| predict.ps2dnormal | Predict function for 'ps2DNormal' |
| predict.ps2dsignal | Predict function for 'ps2DSignal' |
| predict.pspfit | Predict function for 'psNormal', 'psBinomial', 'psPoisson' |
| predict.pssignal | Predict function for 'psSignal' |
| predict.psvcsignal | Predict function for 'psVCSignal' |
| predict.simpsr | Predict function for 'sim_psr' |
| predict.simvcpsr | Predict function for 'sim_vcpsr' |
| ps2DGLM | Two-dimensional smoothing of scattered normal or non-normal... |
| ps2DNormal | Two-dimensional smoothing scattered (normal) data using... |
| ps2D_PartialDeriv | Partial derivative two-dimensional smoothing scattered... |
| ps2DSignal | Two-dimensional penalized signal regression using P-splines. |
| psBinomial | Smoothing scattered binomial data using P-splines. |
| psNormal | Smoothing scattered (normal) data using P-splines. |
| psNormal_Deriv | Derivative for a P-spline fit of scattered (normal) data. |
| pspline2d_checker | P-spline 2D tensor product checking algorithm for the GLM. |
| pspline_checker | P-spline checking algorithm for the GLM. |
| pspline_fitter | P-spline fitting algorithm for the GLM. |
| psPoisson | Smoothing scattered Poisson data using P-splines. |
| psSignal | Smooth signal (multivariate calibration) regression using... |
| psVCSignal | Varying-coefficient penalized signal regression using... |
| rdw | Observations on the widths of red blood cell distributions... |
| rowtens | Compute the row tensor product of two matrices |
| save_PDF | Save a plot as a PDF file. |
| set_panels | Prepare graphics layout for multiple panels |
| set_window | Open a graphics window. |
| sim_psr | Single-Index signal regression using P-splines |
| sim_vcpsr | Varying-coefficient single-index signal regression using... |
| SpATS.nogeno | Two-dimensional P-spline smoothing |
| spbase | Compute a sparse B-spline basis on evenly spaced knots |
| Sugar | Sugar Processing Data |
| Suicide | Suicide Data Set |
| tpower | Compute a truncated power function. |
| Varstar | Brightness of a variable star. |
| Woodsurf | Profile of a sanded piece of wood. |
