Different regularization approaches for Cox Frailty Models by penalization methods are provided.

Estimation of univariate (conditional) densities using penalized B-splines with automatic selection of optimal smoothing parameter.

Implements statistical methods for estimating disease penetrance in 
    family-based studies. Penetrance refers to the probability of disease§
    manifestation in individuals carrying specific genetic variants. The package 
    provides tools for age-specific penetrance estimation, handling missing data, 
    and accounting for ascertainment bias in family studies.
    Cite as: Kubista, N., Braun, D. & Parmigiani, G. (2024) <doi:10.48550/arXiv.2411.18816>.

Fits single- and multiple-group penalized factor analysis models 
    via a trust-region algorithm with integrated automatic multiple tuning 
    parameter selection (Geminiani et al., 2021 <doi:10.1007/s11336-021-09751-8>). 
    Available penalties include lasso, adaptive lasso, scad, mcp, and ridge.

Currently incorporate the generalized odds-rate model (a type of linear 
    transformation model) for interval-censored data based on penalized monotonic B-Spline. 
    More methods under other semiparametric models such as cure model or additive model will
    be included in future versions. For more details see Lu, M., Liu, Y., Li, C. and Sun, J. 
    (2019) <arXiv:1912.11703>.

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).

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.