Version 2.3.3 (2018-11)
  o Added the final estimated model to the 'clustvarsel' object. 
  o Solved a bug that stop execution in the greedy-backward search when no 
    variables could be removed. 

Version 2.3.2 (2018-04)
  o Package version accompanying JSS paper. 
  o Bug fixes in the extreme case no clustering variable is selected using
    the greedy forward/backward search.

Version 2.3.1 (2017-06)
  o Fix bug on a "if" executed with a condition that has length greater than 1.

Version 2.3 (2017-01)
  o Add optional argument 'verbose' to clustvarsel() for printing steps
    info during the search.
  o New print method for 'clustvarsel' objects.
  o A parallel cluster is automatically stopped unless a registered parallel
    back end is provided as argument to 'parallel' argument in the 
    clustvarsel() function call.
  o Add "A quick tour of clustvarsel" vignette.
  
Version 2.2 (2015-11)
  o Reformat summary output from clustvarsel.
  o Add and update references in main help page.

Version 2.1 (2014-10)
  o Version associated with JSS paper submission.
  o Add explicitly stop of clusters if parallel is used.
  o Specifically included in the hc() function call the argument name 'data = ...' 
    so that works with both mclust version 4.4 and upper.
  o Other bug fixes and improvements.

Version 2.0 (2013-10)
  o Partial rewriting of the package.
  o "greedy" search has option for forward and backward direction.
  o "headlong" search has option only for forward direction in this release.
  o G is not the maximum number of clusters but it must be a vector of number
    of cluster to look for.
  o No separate code for samp and nosamp version of each search algorithm.
  o Inclusion of argument hcModel to control the initial hierarchical 
    clustering.
  o Include subset selection in the regression of proposed variable on the 
    variables already included.
  o "greedy" search algorithms can be executed either sequentially or using 
    the parallel computing facilities available in R.
  o This version of the package requires R (>= 3.0.0) and mclust (>= 4.0).
    
Version 1.3 (2009-08)
  o Last version on CRAN available for R-2.14.x and mclust version 3.5