NEWS

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robustHD 0.8.1 (2024-06-30)

• Fix in C++ code for rlars() to avoid elementwise multiplication of row and column vector due to new version of RcppArmadillo being stricter regarding dimensions.
• Minor fix in help file for function coefPlot().

robustHD 0.8.0 (2023-09-26)

• Removed deprecated functions.
• Added rstandard() method for standardized residuals rather than residuals(standardize = TRUE).
• Added DOI's to references in help files.
• Minor change in behavior of diagnosticPlot() for the regression diagnostic plot of sparse LTS results when the number of selected variables is large compared to the number of observations. Added clear documentation why this plot may fail in such a situation.
• Added metainformation on proteins, genes, and cancer cell lines to the NCI-60 cancer cell panel data.
• Bugfix of inconsistent argument names of the internal generic function getComponent() one of its methods.

robustHD 0.7.4 (2023-01-18)

• Bugfix in C++ code: deprecated argument of insert_rows() and insert_cols() no longer used.

robustHD 0.7.3 (2022-08-12)

• Bugfix in sparseLTS(): function calls for fitting the model on training sets (when selecting lambda via prediction error estimation) are now evaluated in the correct environment.

robustHD 0.7.2 (2021-11-23)

• Added CITATION file.
• Added reference to JOSS paper in package help file.
• Added URL and BugReports fields to DESCRIPTION file.

robustHD 0.7.1 (2021-10-13)

• Unit tests are now run automatically with R CMD check.
• Help file of sparseLTS() now correctly documents that arguments for selecting the optimal value of the penalty parameter are ignored if only one value of the penalty parameter is supplied.

robustHD 0.7.0 (2021-09-17)

• Re-implemented plots and added functions setupCoefPlot(), setupCritPlot(), and setupDiagnosticPlot() to extract all the relevant information.
• Removed deprecated functions.
• Function partialOrder() for finding the order of the smallest or largest values of a vector is now exported.
• Added NCI-60 cancer cell panel data.
• Added coef(), fitted(), and residuals() methods for objects of class "perrySeqModel".
• Updated broken links in documentation.

robustHD 0.6.1 (2019-12-14)

• Internal C++ functions for testing are now properly registered.

robustHD 0.6.0 (2019-12-09)

• Method for function weights() is now used to retrieve robustness weights from objects of class "sparseLTS" (with argument type = "robustness").
• C++ functions are now properly registered.
• The alternative back end for sparse least trimmed squares from package sparseLTSEigen is no longer supported and can no longer be used.

robustHD 0.5.1 (2016-01-08)

• 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'.

robustHD 0.5.0 (2014-04-30)

• 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.

robustHD 0.4.0 (2013-12-10)

• 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.

robustHD 0.3.2 (2013-05-02)

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

robustHD 0.3.1 (2013-04-16)

• 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.

robustHD 0.3.0 (2013-03-13)

• 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.

robustHD 0.2.2 (2012-10-30)

• 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.

robustHD 0.2.1 (2012-09-09)

• 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.

robustHD 0.2.0 (2012-08-24)

• 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.