Changes in version 2.6.0                        

  - Fixed an error with the function GibbsBvsF that failed, in certain
    cases, to identify correctly the factors.
  - There was an error in the label of Liangetal that appeared as
    Liangetat

                        Changes in version 2.5.0                        

  - Added the computation of Rao-Blackwell estimations of inclusion
    probabilities. Implemented in GibbsBvs.

                 Changes in version 2.4.5 (2025-01-08)                  

  - Fixed a compilation error reported by CRAN mantainers (Issue 51)

                        Changes in version 2.3.5                        

  - Fixed an error that appears when using the option
    prior.models="User".

                 Changes in version 2.2.5 (2023-03-08)                  

  - Minor changes about the role of the authors of the package.

                        Changes in version 2.2.2                        

  - Included the implementation by Greenaway (2018) of the robust prior,
    and a better organization of the labels to refer to the priors plus
    the need to specify those literally.

                        Changes in version 2.2.1                        

  - Two versions of the intrinsic hyper-g prior are implemented.

                        Changes in version 2.2.0                        

  - the OBICE study is included.

                        Changes in version 2.1.0                        

  - intrinsic prior (by Moreno, Giron and Casella) added to Bvs and
    GibbsBvs.

  - Now calculations of Bayes factors for liang and ZS prior use a
    definition based on the exp(log()) of the expression: quite more
    stable

                 Changes in version 2.0.1 (2020-02-18)                  

  - Minor updates in order to pass CRAN checks.

                        Changes in version 2.0.0                        

  - Added new functionalities to handle the situation with p>n and p>>n

  - Added a new function to handle variable selection with factors that
    is independent on the parameterization (contrast) used to
    parameterize factors and that is able to control for multiplicity.

  - Corrected a numerical error in the computation of Robust Bayes
    factors.

                        Changes in version 1.9.0                        

  - Added en estimation of posterior probabilities of models based on
    the normalizing constant. (it goes with the print function)

                        Changes in version 1.8.2                        

  - Added a vignette based on the R Journal article
    https://journal.r-project.org/archive/2018/RJ-2018-021/index.html.

                        Changes in version 1.8.1                        

  - Added the calculation of the normalizing constant.

                 Changes in version 1.8.0 (2017-12-04)                  

  - Merged Bvs and PBvs in just one function (called Bvs and old PBvs
    disappears). Bvs now has two extra parameters to control
    parallelization: parallel and n.nodes.

  - Several changes in Btest: 1) it now allows for unnamed lists of
    models and if unnamed lists are provided, default names are given by
    the function. 2) The prior probabilities argument priorprobs does
    not have to be named (by default the order of the models in argument
    models is used). 3) Deprecated argument relax.nest, replaced by the
    explicit definition of the null model by the user via the argument
    null.model

  - In Bvs and GibbsBvs the order of arguments has slightly changed and
    now data is the second argument followed by formula.

  - Now plotBvs is a S3 function defined as plot.Bvs

  - Now predictBvs is a S3 function defined as predict.Bvs

  - In Bvs the argument fixed.cov is deprecated, now replaced by the
    formula for the null model in the argument null.model

  - Option "trace" added to plot

  - print updated to show the 10 most probable models (among the
    visited) for method Gibbs

  - removed the comment at initialization

  - BMAcoeff no longer shows the graphic for all the variables, instead
    use histBMA to plot the posterior distribution of the coefficients.