Changes in robustHD version 0.5.1

    + Explicitly calling C++ function std::abs() rather than abs() to avoid
      clang warning.

    + Correctly importing functions head() and tail() from package 'utils' and
      function devAskNewPage from package 'grDevices'.



Changes in robustHD version 0.5.0

    + Added functionality for (robust) groupwise least angle regression.

    + Added TopGear car data.

    + Diagnostic plots now allow to pass arguments to covMcd().

    + Removed PCA step from data cleaning RLARS to consolidate code.

    + Updated package dependencies.



Changes in robustHD version 0.4.0

    + sparseLTS() no longer uses subsampling algorithm in the special case of
      alpha = 1.

    + sparseLTS() now has argument 'normalize' to specify whether the predictor
      variables should be normalized.

    + sparseLTS() now computes objective function with coefficients for
      normalized data (if applicable).

    + Most required packages are now imports rather than depends.



Changes in robustHD version 0.3.2

    + Bugfixes in sparseLTS() preventing errors for high-dimensional data.


Changes in robustHD version 0.3.1

    + rlars now uses perryFit() instead of perryTuning() for prediction error
      estimation.

    + Bugfix in rlars() allowing the number of variables to be sequenced to be
      larger than half the number of observations.

    + Bugfix in sparseLTS() in case of only one predictor variable.

    + Added tests for C++ implementation of the lasso.


Changes in robustHD version 0.3.0

    + Redesign of the class structure.

    + Redesign of how C++ back end is called.

    + Functionality of sparseLTSGrid() now included in sparseLTS();
      sparseLTSGrid() is now a deprecated wrapper function.

    + Restructured internal code for computing initial subsets for sparse LTS.

    + rlars() now supports data cleaning RLARS, with an extra PCA step for
      high-dimensional data.

    + New argument 's' in rlars() to select the steps along the sequence for
      which to compute submodels

    + fortify() and diagnosticPlot() methods for class "seqModel".

    + Bugfix in predict() method for "sparseLTS" if object was computed without
      intercept.



Changes in robustHD version 0.2.2

    + Bugfix in sparseLTS() for more stability of the results.

    + Bugfix in winsorize(): weights are now correctly returned as vector for
      a matrix with only one column.

    + Bugfix in diagnosticPlot(): previous setting of devAskNewPage() is now
      retained on exit.


Changes in robustHD version 0.2.1

    + Bugfix in rlars(): formula method now only adds function call and model
      terms if the default method returns an "rlars" object, not if only the
      sequence is returned.

    + Bugfix in rlars(): argument cl is now preferred over argument ncores for
      parallel computing, as stated in the help file.

    + Plots are no longer using the opts() function from package ggplot2, which
      is deprecated since ggplot2 version 0.9.2.


Changes in robustHD version 0.2.0

    + Graphics are now based on package ggplot2 instead of lattice.

    + Prediction error estimation is now based on package perry instead of
      cvTools.

    + Parallel computing for sparseLTS() now available via OpenMP.

    + rlars() is now using C++ code for variable sequencing, including
      parallelization of certain tasks via OpenMP.  Further parallel
      computing is implemented on the R level via package parallel.

    + sparseLTSGrid() and rlars() now allow model selection based on the
      prediction error.

    + coef(), fitted(), residuals() and wt() methods now have argument
      'drop' to control whether to reduce the dimension if possible.

    + Renamed components 'weight' and 'raw.weights' of sparse LTS models to
      'wt' and 'raw.wt', and renamed the accessor function accordingly to wt().

    + Print methods for "sparseLTS" and "sparseLTSGrid" now only show non-zero
      coefficients by default; also added argument to print method for "rlars".

    + sparseLTS() and sparseLTSGrid() now store the raw fitted values.

    + Bugfixes in C++ code for sparseLTS() and fastLasso() to prevent memory
      related errors.
