Flexible Pair-Copula Estimation in D-vines with Penalized
Splines
R (>= 2.11.0), lattice, quadprog, doMC, TSP, fda
Flexible Pair-Copula Estimation in D-vines with Penalized
Splines.

Flexible Pair-Copula Estimation in D-vines using Bivariate
Penalized Splines
R (>= 2.15.1), lattice, quadprog, TSP, fda, Matrix
Flexible Pair-Copula Estimation in D-vines using Bivariate
Penalized Splines.

Flexible Pair-Copula Estimation in D-Vines using Bivariate
Penalized Splines
R (>= 2.15.1), lattice, TSP, fda, Matrix, foreach
Flexible Pair-Copula Estimation in D-vines using Bivariate Penalized Splines.

R (>= 2.11.0), lattice, quadprog, TSP, fda

Estimating regularized multistate models using L1 penalties.
This package provides features for L1 penalized estimation of multistate models with the penalty applied to absolute effects and absolute effect differences (i.e., effects on transition-type specific hazard rates).

Estimating Regularized Multi-state Models Using L1 Penalties
Structured fusion Lasso penalized estimation of multi-state models with the penalty applied to absolute effects and absolute effect differences (i.e., effects on transition-type specific hazard rates).

Variable Selection in PH Cure Model with Time-Varying Covariates
c(person(given = "Alessandro",
family = "Beretta",
role = c("aut", "cre"),
email = "a.beretta@uliege.be",
comment = c(ORCID = "0000-0002-0427-8785")),
person(given = "Cédric",
family = "Heuchenne",
role = "aut",
comment = c(ORCID = "0000-0002-3150-3044")))
Implementation of the semi-parametric proportional-hazards (PH) of Sy and Taylor (2000) <doi:10.1111/j.0006-341X.2000.00227.x> extended to time-varying covariates. Estimation and variable selection are based on the methodology described in Beretta and Heuchenne (2019) <doi:10.1080/02664763.2018.1554627>; confidence intervals of the parameter estimates may be computed using a bootstrap approach. Moreover, data following the PH cure model may be simulated using a method similar to Hendry (2014) <doi:10.1002/sim.5945>, where the event-times are generated on a continuous scale from a piecewise exponential distribution conditional on time-varying covariates.
Copyright (C) 2019 University of Liège (Belgium).
Alessandro Beretta [aut, cre] (<https://orcid.org/0000-0002-0427-8785>),
Cédric Heuchenne [aut] (<https://orcid.org/0000-0002-3150-3044>)