Improves stability when fitting Fine-Gray model with longitudinal covariates.
Enables parallel computation for cross-validation.
Fixes several bugs as reported in Issues.
Adding options to use user-specified pseudo counts
Adding options to use user-specified number of maximum number of iterations
Adding a simulation scenario for survival regression models with longitudinal features
(BETA version of) the new GEE method
Including more examples in document compared to CRAN version (0.1.0.9000)
Enables elastic net models. Users can specify the weight of lasso
penalty using argument a. (0.1.0.9001)
Allows adding non-compositional covariates which are not constrained by the zero-sum constraint. (0.1.0.9001)
Adds a function mcv.FLORAL() to perform multiple
runs of k-fold cross-validation to summarize selection probabilities for
features. (0.1.0.9001)
Adds a function a.FLORAL() to compare different
choices of elastic net weight a for a fixed
cross-validation setting. (0.1.0.9001)