Companion release to the Journal of Statistical Software
publication: Baştürk et al. (2026), “BayesMultiMode: Bayesian Mode
Inference in R”, JSS 116(3), doi:10.18637/jss.v116.i03.
Added inst/CITATION pointing to the JSS article.
Added the JSS reference to the DESCRIPTION and to the bayes_fit()
and bayes_mode() documentation.
Version 0.7.5
Fixed issue with cross-platform reproducibility.
Version 0.7.4
Updated following following ggplot new version.
Version 0.7.2
Added conditional_nb_modes argument to bayes_mode()
Improved the gibbs algorithm for the skew normal
Fixed bug with inside_range
Added message for users to be aware of potential label-switching to
summary and plot_trace functions.
Minimum version for ggplot2 dependency.
Version 0.7.1
Range argument not optional any more when plotting mixtures
More details in summary methods
Added a df to the mode output showing the mixture density in each
draw
Added message for users to be aware of potential label-switching to
summary and plot_trace functions.
Version 0.7.0
Major changes around the structure of the package
bayes_estimation() renamed to bayes_fit()
new_BayesMixture() renamed to bayes_mixture()
Added a class “mixture” representing estimated mixtures which is
used as input to mode estimation functions; see mixture()
Added mix_mode() which calls the mode finding algorithms;
discrete_MF, fixed_point and MEM have been removed
Added a class “mix_mode”
Removed the plotting option inside the mode estimation
functions
Added print, plot and summary methods for all classes.
Version 0.6.0
Added examples to new_BayesMixture() and bayes_mode()
Fixed typo on the tolerance arguments
Added details to mode and mixture estimation functions
Improved the documentation
Version 0.5.1
Improved robustness of the gibbs sampler when initial classification
is bad
Version 0.5.0
Restructured the code to make use of S3 generic functions plot() and
summary()