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#  News: to package distrEx
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v 1.9 
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* 'distrEx' now behaves exactly the same as the other members
  of the distrXXX family as to 'distrExOptions()', 'getdistrExOption()'

* substantial contributions by Jay Kerns, gkerns@ysu.edu:
  + skewness & kurtosis are now available as functionals
  + E(), var() return NA in case of T-distribution if not defined

* disclaimer for possible collisions with other definitions of
  kurtosis and skewness

* added note on masking on startup as well as disrExMASK()

* enhanced 'illustrateCLT'
  + plot includes a title
  + for 'DiscreteDistributions' in the "d"-panel, the support is thinned
    out if length too long
  + Komogoroff-distance is printed out
  + 'illustrateCLT' no longer is a generic function but a regular function
  + the plotting feature of 'illustrateCLT' is extracted and has become 
    a generic function 'plotCLT' (now with title and the summands mentioned
    in the header) 
  + there is a TclTk-based demo now (therefore TclTk is a suggested package now)
    replaced recursive summation in illustrate-CLT method by 'convpow'

* new demo 'illustLLN' and function 'illustrateLLN'
  + preset strings similar to those of plot-methods from package 'distr'

* moved some parts from package 'distrEx' to package 'distr' 
   + generating function 'DiscreteDistribution' 
   + univariate methods of 'liesInSupport()' 
   + classes 'DistrList' and 'UnivariateDistrList'
   + generating functions EuclideanSpace() ,Reals(), Naturals() 

* mentioned in package-help: startup messages may now also be suppressed by
  suppressPackageStartupMessages() (from package 'base')

* adapted demo() to comply with change in return value of require()
  from R-2.5.0patched on

* formals for slots p,q,d as in package stats to enhance accuracy

    + p(X)(q, [cond,] lower.tail = TRUE, log.p = FALSE)
    + q(X)(p, [cond,] lower.tail = TRUE, log.p = FALSE)
    + d(X)(x, [cond,] log = FALSE)
    
    used wherever possible;
    but backwards compatibility: 
        always checked whether lowert.tail / log / log.p are formals

 * some exact formulas for mad, median, and IQR  
 * new method for IQR for DiscreteDistributions taking care that between upper and lower
   quartile there is 50% probability 
 * E-, var-, IQR-, mad-, median-, kurtosis-, skewness- methods 
   for new class union AffLinDistribution

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v 1.8 
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* changed to version counting of the remaining distrXXX packages
* corrected minor error in E() and var() method for Nbinom 
  (thanks to Spencer Graves for drawing our attention to this)
* fixed error in definition of  Hellinger distance (HellingerDist)

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v 0.4-4 
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* dim() method for DiscreteMVDistribution 
* var() + E() overloaded for DExp-Class 
* sd()-method  overwritten for Norm-Class to allow function / condition argument

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v 0.4-3 
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*  Implementation of functionals:
   o evaluation of exact expressions of E (expectation functional) for most specific distributions from stats package
   o var, sd methods for UnivariateDistributions; these include calls like

     N <- Norm()

     var(N,function(t)abs(t)^(1/2))   # calculates Var[|N|^(1/2)] 

     also (factorized) conditional variance is available
   o evaluation of exact expressions of var for most specific distributions from stats package
   o median, IQR, mad methods for UnivariateDistributions
   o for var, sd, median, IQR, mad: all functionality/arguments of stats methods is/are preserved and
            only if first argument / argument x is of class UnivariateDistribution (or descendant) a 
            different method is applied
* Internationalization: use of gettext, gettextf in output
* C-interface .GLaw() to replace respective R-Code in distrExintegrate.R
* PrognCondDistribution, PrognCondition are included as classes and generating functions (incl. show-method); 
* Inclusion of demos (see above)
  + PrognCondDistribution, PrognCondition are included as classes and generating functions (incl. show-method); 
  + illustrateCLT is included and rd-file is done


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v 0.4-2 
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* ContaminationSize, HellingerDist, KolmogorovDist, TotalVarDist now return a list which consists of the corresponding distributions and their distance
* minor changes in m1df and m2df to increase speed of computation
* minor changes in DiscreteMVDistribution to increase speed of computation
* introduction of a new parameter useApply in methods for function E with default value TRUE