Implements the Differential Evolution algorithm for global
    optimization of a real-valued function of a real-valued parameter
    vector as described in Mullen et al. (2011) <doi:10.18637/jss.v040.i06>.

Differential Evolution (DE) stochastic heuristic algorithms for
    global optimization of problems with and without general constraints.
    The aim is to curate a collection of its variants that
    (1) do not sacrifice simplicity of design,
    (2) are essentially tuning-free, and
    (3) can be efficiently implemented directly in the R language.
    Currently, it provides implementations of the algorithms 'jDE' by
    Brest et al. (2006) <doi:10.1109/TEVC.2006.872133> for single-objective
    optimization and 'NCDE' by Qu et al. (2012) <doi:10.1109/TEVC.2011.2161873>
    for multimodal optimization (single-objective problems with
    multiple solutions).

Hash an expression with its dependencies and store its
	value, reloading it from a file as long as both the expression and
	its dependencies stay the same.

Dependent censoring regression models for survival multivariate data. These models are based on extensions of the frailty models, capable to accommodating the dependence between failure and censoring times, with Weibull and piecewise exponential marginal distributions. Theoretical details regarding the models implemented in the package can be found in Schneider et al. (2019) <doi:10.1002/bimj.201800391>.

Several statistical methods for analyzing survival data under various forms of dependent
    censoring are implemented in the package. In addition to accounting for dependent censoring, it 
    offers tools to adjust for unmeasured confounding factors. The implemented approaches allow 
    users to estimate the dependency between survival time and dependent censoring time, based 
    solely on observed survival data. For more details on the methods, refer to Deresa and Van 
    Keilegom (2021) <doi:10.1093/biomet/asaa095>, Czado and Van Keilegom (2023)
    <doi:10.1093/biomet/asac067>, Crommen et al. (2024) <doi:10.1007/s11749-023-00903-9>
    and Willems et al. (2024+) <doi:10.48550/arXiv.2403.11860>.