Multidimensional Penalized Splines for Survival and Net Survival Models

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 |

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 |

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