clustvarsel 2.3.5 (2025-04)

• Explicitly uses current value of mclust.options("hcUse") for initializing the EM iterative estimation process.
• Fixed anchors in Rd \link{} targets that were not within the package, addressing CRAN requirements.

clustvarsel 2.3.4 (2020-12)

• Bug fixes and polish.

clustvarsel 2.3.3 (2018-11)

• Added the final estimated model to the clustvarsel object.
• Solved a bug that stop execution in the greedy-backward search when no variables could be removed.

clustvarsel 2.3.2 (2018-04)

• Package version accompanying JSS paper.
• Bug fixes in the extreme case no clustering variable is selected using the greedy forward/backward search.

clustvarsel 2.3.1 (2017-06)

• Fix bug on a if executed with a condition that has length greater than 1.

clustvarsel 2.3 (2017-01)

• Add optional argument verbose to clustvarsel() for printing steps info during the search.
• New print method for clustvarsel objects.
• A parallel cluster is automatically stopped unless a registered parallel back end is provided as argument to parallel argument in the clustvarsel() function call.
• Add “A quick tour of clustvarsel” vignette.

clustvarsel 2.2 (2015-11)

• Reformat summary output from clustvarsel object.
• Add and update references in main help page.

clustvarsel 2.1 (2014-10)

• Version associated with JSS paper submission.
• Add explicitly stop of clusters if parallel is used.
• Specifically included in the hc() function call the argument name data = ... so that works with both mclust version 4.4 and upper.
• Other bug fixes and improvements.

clustvarsel 2.0 (2013-10)

• Partial rewriting of the package.
• “greedy” search has option for forward and backward direction.
• “headlong” search has option only for forward direction in this release.
• In clustvarsel() argument G is not the maximum number of clusters but it must be a vector of number of cluster to look for.
• No separate code for sampling and no-sampling version of each search algorithm.
• Inclusion of argument hcModel to control the initial hierarchical clustering.
• Include subset selection in the regression of proposed variable on the variables already included.
• “greedy” search algorithms can be executed either sequentially or using the parallel computing facilities available in R.
• This version of the package requires R (>= 3.0.0) and mclust (>= 4.0).

clustvarsel 1.3 (2009-08)

• Last version on CRAN available for R-2.14.x and mclust version 3.5