| colSums2 | colSums of a matrix |
| constraint | Sum-to-zero constraint |
| cor.var | Implementation of the corrected variance Vc |
| crs | Bases for cubic regression splines (equivalent to "cr" in... |
| crs.FP | Penalty matrix constructor for cubic regression splines |
| datCancer | Patients diagnosed with cervical cancer |
| deriv_R | Derivative of a Choleski factor |
| design.matrix | Design matrix for the model needed in Gauss-Legendre... |
| grad_rho | Gradient vector of LCV and LAML wrt rho (log smoothing... |
| grapes-cross-grapes | Matrix cross-multiplication between two matrices |
| grapes-mult-grapes | Matrix multiplication between two matrices |
| grapes-vec-grapes | Matrix multiplication between a matrix and a vector |
| Hess_rho | Hessian matrix of LCV and LAML wrt rho (log smoothing... |
| instr | Position of the nth occurrence of a string in another one |
| inv.repam | Reverses the initial reparameterization for stable evaluation... |
| model.cons | Design and penalty matrices for the model |
| NR.beta | Inner Newton-Raphson algorithm for regression parameters... |
| NR.rho | Outer Newton-Raphson algorithm for smoothing parameters... |
| predict.survPen | Hazard and Survival prediction from fitted 'survPen' model |
| print.summary.survPen | print summary for a 'survPen' fit |
| pwcst | Defining piecewise constant (excess) hazard in survPen... |
| rd | Defining random effects in survPen formulae |
| repam | Applies initial reparameterization for stable evaluation of... |
| smf | Defining smooths in survPen formulae |
| smooth.cons | Design and penalty matrices of penalized splines in a... |
| smooth.cons.integral | Design matrix of penalized splines in a smooth.spec object... |
| smooth.spec | Covariates specified as penalized splines |
| summary.survPen | Summary for a 'survPen' fit |
| survPen | (Excess) hazard model with (multidimensional) penalized... |
| survPen.fit | (Excess) hazard model with multidimensional penalized splines... |
| survPenObject | Fitted survPen object |
| tensor.in | tensor model matrix for two marginal bases |
| tensor.prod.S | Tensor product for penalty matrices |
| tensor.prod.X | tensor model matrix |
