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clustvarsel 2.3.5 (2021-11) NOT ON CRAN

  • Explicitly defines to use current value of mclust.options("hcUse") for initialization of models estimation.

clustvarsel 2.3.4 (2020-12)

CRAN release: 2020-12-16

  • Bug fixes and polish.

clustvarsel 2.3.3 (2018-11)

CRAN release: 2018-11-19

  • 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)

CRAN release: 2018-04-09

  • 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)

CRAN release: 2017-07-07

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

clustvarsel 2.3 (2017-01)

CRAN release: 2017-02-24

  • 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)

CRAN release: 2015-11-19

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

clustvarsel 2.1 (2014-10)

CRAN release: 2014-10-15

  • 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)

CRAN release: 2013-10-25

  • 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)

CRAN release: 2009-08-04

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