Changes in version 0.4.11 (2025-12-08)                 

  - Add a new function slide that supports Ising model reconstruction
  - The maintainer's changed from zhuj37@mail2.sysu.edu.cn to
    zhuj1jqx@gmail.com.

                 Changes in version 0.4.10 (2025-04-05)                 

  - Fix note in NOTE about possible bashisms.

                 Changes in version 0.4.9 (2024-09-09)                  

  - Fix bug in Cpp level
  - Fix error in: https://www.stats.ox.ac.uk/pub/bdr/clang19/abess.log
  - Fix notes in
    https://cran.r-project.org/web/checks/check_results_abess.html

                 Changes in version 0.4.8 (2023-09-19)                  

  - Support no-intercept GLM model by param 'fit.intercept'.
  - Allow to restrict the range of estimation for beta by param
    'beta.high' and 'beta.low'.
  - Add cite message when load 'abess'.
  - Fix a bug when support.size is 0.

                 Changes in version 0.4.7 (2023-02-19)                  

  - Allow the other criterion for model selection: AUC for (multinomial)
    logistic regression such as the area under the curve (AUC).
  - Simplify the C++ code structure.
  - Fix note "Specified C++11: please update to current default of
    C++17" in CRAN.

                 Changes in version 0.4.6 (2022-11-06)                  

  - Adapt to the API change of the Matrix package.
  - Change the package structure such that the API functions can reuse
    the utility function. It facilitates the testing for package.
  - Update citation information.

                 Changes in version 0.4.5 (2022-03-22)                  

  - Support generalized linear model for ordinal response, also named as
    rank learning in machine learning community.
  - Support robust principal analysis
  - Modify R package structure to make many internal components are
    reusable.
  - Update README.md

                 Changes in version 0.4.0 (2021-12-08)                  

  - Support generalized linear model when the link function is Gamma
    distribution. By setting family = "gamma" in abess function, users
    can analyze the dataset with a positive valued and skewed response.
  - Support flexible support size for sequential principal component
    analysis (PCA), accompanied with several helpful generic function
    like plot.
  - Support user-specified cross validation division for abess and
    abesspca function by additional argument foldid.
  - Support robust principal component analysis now. A new R function
    abessrpca can access it.
  - Improve the R package document by: adding more details and giving
    more links related to core functions.

                 Changes in version 0.3.0 (2021-09-03)                  

  - Add docs2search for R's website
  - Support important searching to improve computational efficiency when
    dimension is 10,000.

                 Changes in version 0.2.0 (2021-07-31)                  

  - Support sparse matrix as input
  - Support golden section search for optimal support size
  - Support ridge-regularized penalty as a generic component
  - Support group subset selection as a generic component
  - Best subset selection for principal component analysis via abesspca
  - Bug fixed

                 Changes in version 0.1.0 (2021-04-21)                  

  - Initial stable version abess package
  - Support best subset selection for linear regression, logistic
    regression, poisson regression, cox proportional hazard regression,
    multi-gaussian regression, multi-nominal regression.
  - Support nuisance selection as a generic component
  - Unified API for cross validation and information criterion to select
    the optimal support size.
  - A documentation website is support for abess package