## ========
Version 1.5

New functions:
  - assoc.twocat(): measures the association between two categorical variables
  - assoc.catcont(): measures the association between a categorical variable and a continuous variable
  - catdesc(): measures the association between a categorical variable and some continuous and/or categorical variables
  - condesc(): measures the association between a continuous variable and some continuous and/or categorical variables}
  - ggcloud_indiv(): cloud of individuals using ggplot
  - ggcloud_variables(): cloud of variables using ggplot
  - ggadd_supvar(): adds a supplementary variable to a cloud of variables using ggplot
  - ggadd_interaction(): adds the interaction between two variables to a cloud of variables using ggplot
  - ggadd_ellipses(): adds concentration ellipses to a cloud of individuals using ggplot

Changes in existing functions:
  - conc.ellipses(): additional options
 

## ========
Version 1.4

New functions:
  - translate.logit(): translates logit models coefficients into percentages
  - tabcontrib(): displays the categories contributing most to MCA dimensions

Changes in existing functions:
  - varsup(): with csMCA, the length of variable argument can be equal to the size of the cloud or the subcloud
  - textvarsup(): with csMCA, the length of variable argument can be equal to the size of the cloud or the subcloud
  - conc.ellipse(): with csMCA, the length of variable argument can be equal to the size of the cloud or the subcloud
  - plot.multiMCA(): 'threshold' argument, aimed at selecting the categories most associated to axes
  - plot.stMCA(): 'threshold' argument, aimed at selecting the categories most associated to axes


## ========
Version 1.3

Changes in existing functions:
  - dimdesc.MCA(): now uses weights

Bug fixes:
  - dimdesc.MCA(): problem of compatibility next to a FactoMineR update


## ========
Version 1.2

New functions:
  - dimvtest(): computes test-values for supplementary variables

Changes in existing functions:
  - dimeta2(): now allows 'stMCA' objects


## ========
Version 1.1

New functions:
  - wtable(): works as table() but allows weights and shows NAs as default
  - prop.wtable(): works as prop.table() but allows weights and shows NAs as default

Changes in existing functions:
  - multiMCA(): RV computation is now an option, with FALSE as default,
    which makes the function execute faster

Bug fixes:
  - textvarsup(): there was an error with the supplementary 
    variable labels when resmca was of class "csMCA".

Error fixes:
  - textvarsup(): plots supplementary variables on the cloud of categories (and not
    the cloud of individuals as it was mentioned in help).