Changes in Version 1.0-4

  o replaced depriciated C-function finite() with isfinite()


Changes in Version 1.0-3
  
  o updated contact information


Changes in Version 1.0-1
  
  o Added argument 'type' to crch() which can be set to "crps" for parameter
    estimation with minimum CRPS instead of maximum likelihood. 

  o Added S3 method of crps() from scoringRules for "crch" objects.

  o Improvements for the predict() method:
    - new types "parameter", "density", "probability", and "crps"
    - with type="response" now the expected value and not the location 
      parameter is returned (not equal for censored and truncated 
      distributions). For better backward compatibility, the default type is
      set to "location".

  o Added pit(), rootogram(), and simulate() methods for crch objects.

  o Changed argument names mean and sd to location and scale in logistic and
    student-t distribution functions 

  o Added new function "crch.stabsel" for stability selection based on    
    "crch.boost.fit". Small S3 methods for the returned class "stabsel.crch"
    are also provided.
  

Changes in Version 1.0-0
  
  o New release accompanying the R-Journal paper: "Heteroscedastic Censored 
    and Truncated Regression with crch" by Messner, Mayr, and Zeileis
    which appears as R-Journal 8(1). See also citation("crch"). 
    
  o Added estfun() method for crch objects


Changes in Version 0.9-2
  
  o The crch() function now supports coefficient optimization by
    boosting to automatically select the most relevant input variables 
    in high dimensional data settings. Extractor and plotting functions 
    for corresponding crch.boost objects are also available.

  o Transferred functions to estimate density, distribution, score, and 
    Hessian matrices to C-code to accelerate coefficient optimization.

  o Added option to crch() to avoid computation of covariance matrix

  o Added left and right arguments to predict.crch() and 
    predict.crch.boost() to allow quantile predictions for non-constant 
    censoring or truncation points.


Changes in Version 0.9-1

  o Added model.matrix() and model.frame() methods for crch objects

  o Bug Fix in predict.crch(): In previous versions predictions for 
    models with other link functions than the log gave wrong results


Changes in Version 0.9-0

  o Added vignette to introduce the crch() function with some
    theoretical background and an illustrating example:
    vignette("crch", package = "crch")

  o The crch() function now also supports truncated responses.
    Furthermore added a wrapper function trch() to fit truncated
    regression models.

  o crch(): Analytical gradients and Hessian matrices are provided for most 
    models to speed up maximum likelihood optimization
    (not available for student-t distribution with degrees of freedom
    estimation).  

  o crch(): For the scale model a link function can now be specified
    (log, identity, or quadratic). In previous version only the log
    was supported.

  o Added functions for probability density, cumulative distribution, 
    random numbers, and quantiles for censored and truncated normal, 
    logistic, and student-t distributions.

  o The residuals() method for crch objects now also provides quantile 
    residuals (Dunn and Smyth 1996).

  o Added update() method for crch objects.


Changes in Version 0.1-0

  o First official release of the package on CRAN. See citation("crch")
    for the accompanying manuscripts. Note that the interface of both
    crch() and hxlr() is still under development and might change in
    future versions of the package.
