NEWS
sharp 1.4.6 (2024-02-03)
sharp 1.4.5 (2024-01-22)
- Allow for alternative optimisation methods implemented in nloptr
- Update parallelisation, now using the future package
- Fix the formatting of continuous outcome in VariableSelection()
- Update the vignette
sharp 1.4.4 (2023-10-21)
- Update references with published articles
sharp 1.4.3 (2023-08-27)
- Add sparse K means from the R package sparcl
- Allow for missing values in proportions for more flexibility
sharp 1.4.2 (2023-06-09)
- Remove functions depending on regsem (removed from CRAN)
- Fix the use of packages in Suggests in the examples
sharp 1.4.1 (2023-05-31)
- Add package vignette
- Use Ridge regression calibrated by cross validation instead of unpenalised regression in Refit(), ExplanatoryPerformance() and
Incremental()
- Add new S3 class structural_model
- Fix inclusion of unpenalised predictors in Incremental()
- Fix clustering of rows in Clustering()
sharp 1.4.0 (2023-04-18)
- Update the stability score used by default (n_cat=NULL), previous score can be used with n_cat=3
- Add new functions for structural equation modelling including StructuralModel(), PenalisedSEM(), PenalisedOpenMx(),
PenalisedLinearSystem(), LavaanModel(), LavaanMatrix(), OpenMxModel(), OpenMxMatrix() and LinearSystemMatrix()
- Add new function CART() for classification and regression trees
- Add the option to run randomised or adaptive lasso in PenalisedRegression()
- Fix a bug when running multinomial lasso with predictors with null variance in the subsamples
- Fix a bug where additional parameters in ... were used in glm.control() within Refit()
sharp 1.3.0 (2023-01-17)
- Add new functions for consensus clustering including Clustering(), Clusters(), ConsensusMatrix(), ClusteringPerformance() and more
- Add new print(), plot() and summary() functions
- Update plotting functions
- Fix parallelisation using argument n_cores in main functions
- Remove duplicated messages in ExplanatoryPerformance()
- Allow for factor ydata in VariableSelection() and related functions
sharp 1.2.1 (2022-12-09)
- Update examples for use with fake 1.3.0
- Fix requirements on input data format in Refitting()
- Add resampling argument in Explanatory()
- Add optional beep at the end of the run in main functions
- Increase igraph vertex size in Graph() and plot()
sharp 1.2.0 (2022-08-15)
- Add the functions Ensemble() and EnsemblePredictions() to build and predict from an ensemble model for VariableSelection()
- Add S3 classes including coef() and predict() for VariableSelection()
- Rename Recalibrate() as Refit()
- Fix use of CPSS in GraphicalModel()
- Fix maximisation of the contrast
- Add simulation functions to the companion R package fake
sharp 1.1.0 (2022-06-17)
First release of stability selection methods and simulation models.