Changes in version 0.7.0 (2026-02-07)                  

  - Minor changes according to dplyr update.
  - Since the survcomp package is no longer supported by CRAN, a
    replacement was made using the survival package's concordance
    function.
  - If you find any issues with the updated concordance index
    calculation, please kindly report on GitHub. Thanks!

                 Changes in version 0.6.0 (2025-11-22)                  

  - Removing dependencies with R package ast2ast.

                 Changes in version 0.5.0 (2025-07-13)                  

  - Adding instructions to install the package via bioconda.

  - Address new CRAN requirements regarding Internet access.

                 Changes in version 0.4.0 (2025-02-17)                  

  - Adding a function phy_to_floral_data which helps convert a phyloseq
    object to be compatible with FLORAL.

  - Adding a corresponding vignette for phy_to_floral_data.

  - Introducing the new GEE model for longitudinal continuous and binary
    outcomes. More documentations to follow in the next development
    version.

                 Changes in version 0.3.0 (2024-08-20)                  

  - 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

                 Changes in version 0.2.0 (2023-07-05)                  

  - 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)

                 Changes in version 0.1.0 (2023-05-11)                  

  - Initial release.