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| NEWS | R Documentation |
Remove dependency on speedglm as this package will be removed from CRAN on 31st March 2023.
Change C++ standard from C++14 to C++17 (default for R 4.3.0).
Fix bug with ifelse and NULL when computing GLM penalty weights for a design matrix with full rank (#7).
Add rmarkdown to the Suggests field in the DESCRIPTION file to avoid problems with knitr version >= 1.32.
Remove 'LazyData' from DESCRIPTION file as no data directory is present.
Only apply ridge penalty to relevant predictors when determining GLM penalty weights.
Correctly determine if the design matrix has full rank.
Optimal values of lambda, in examples and vignette, are re-determined after changes in computation of GLM penalty weights.
Use C++14 (instead of C++11) which requires R version 3.4 or higher.
glmsmurf: Check that factors have at least two levels.
Update Devriendt et al. (2021) reference.
R-code:plot_lambda: Properly check whether the object x of class glmsmurf contains components related to the selection of the sparsity parameter lambda.
Use named families for glmnet whenever possible as this is faster.
R-code: Require at least version 4.0 of glmnet as this allows for more families to be used.
plot.glmsmurf, plot_reest.glmsmurf and plot_lambda.glmsmurf: Link to plot.default instead of plot (graphics) to avoid warnings on R-4.0.0.
R-code:Use numerical tolerance that is also suitable on platforms without a long double.
Use five-fold instead of two-fold cross-validation in tests.
Use rent dataset from catdata again as this package will no longer be archived.
Use default date format for vignette date.
R-code:Adapt test for input for prior weights to catch multiple warnings.
Use only one core to select the optimal value of lambda in the example of plot_lambda.
R-code:Add extra tests for proximal operators, number of cross-validation folds and prior weights.
Add rent dataset from catdata as this package is scheduled to be archived on CRAN on 14 February 2020.
Correct README to display correct pipeline status on GitLab.
R-code: Select first element of class(obj) when obj might be a matrix object as matrix objects will also inherit from class array in R 4.0.0 (and hence class(obj) will be of length > 1).
Add an extra test for the output of a glmsmurf object where a Graph-Guided Fused Lasso is used.
Update to roxygen2 version 7.0.0.
Add empty first line to Rent_example2.R to avoid problems with roxygen2 version 7.0.0.
Move example files from /inst to /inst/examples.
R-code:glmsmurf: Improve handling of coefficient names.
plot_lambda: Replace \dontrun by \donttest as requested by CRAN.
R-code:p: change order of group and refcat arguments.
glmsmurf: catch errors when computing the maximum value of lambda (#2).
Fix bug in standardization when a continuous predictor is penalized with a Lasso or Group Lasso penalty (#4).
Move examples for S3 methods into example for glmsmurf.
Remove maintainer field in DESCRIPTION as it is already set using Authors@R.
Change GitLab URL in README.
Update Devriendt et al. (2018) reference.
Add reference to Devriendt et al. (2018) in DESCRIPTION.
First release on CRAN.
First public release on GitLab.
R-code:glmsmurf: Use "cv1se" to indicate selection of lambda using cross-validation with the one standard error rule. E.g. "cv.dev.1se" is renamed to "cv1se.dev".
glmsmurf: Add note that selected value of lambda for out-of-sample selection and cross-validation is not (always) deterministic.
General documentation updates.
Add continuous integration (CI) on GitLab.
Add tests for plot, plot_lambda and summary functions.
Add tests for elements of glmsmurf-class related to selection of lambda.
General vignette update.
Add LICENSE file.
First release on GitLab.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.