Add vignette for Random Forest Survival Analysis and update DESCRIPTION#68
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- Introduced a comprehensive vignette detailing the workflow for random survival forest analysis using the PBC dataset. - Included sections on data preparation, exploratory data analysis, model fitting, variable selection, and visualization techniques. - Added references to relevant literature in a new bibliography file.
…ss known issues with partial dependence plots
Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #68 +/- ##
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- Coverage 84.73% 83.59% -1.14%
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Files 24 25 +1
Lines 1801 2005 +204
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+ Hits 1526 1676 +150
- Misses 275 329 +54
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…or handling for missing package
…date test cases for randomForest, and add codecov configuration
- Updated `plot.gg_survival` to automatically handle raw `rfsrc` objects. - Deprecated `surv_partial.rfsrc` in favor of `gg_partial_rfsrc`, with appropriate warning messages. - Enhanced documentation for `gg_survival`, `gg_partial_rfsrc`, and related functions to clarify usage and parameters. - Added new plotting methods for `gg_partial`, `gg_partial_rfsrc`, and `gg_partialpro` to streamline visualization of partial dependence curves. - Improved test coverage for new plotting functions and ensured deprecation warnings are handled in tests. - Updated vignettes to reflect changes in function usage and provide examples for new plotting capabilities.
…nd update pkgdown configuration to include new plot methods
…scalar_int helper for improved error handling
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This pull request introduces several improvements and fixes across documentation, CI workflows, package metadata, and the
gg_partial_rfsrcfunction. The most significant change is a major enhancement togg_partial_rfsrc, which now automatically handles time point alignment for survival forests and allows for more efficient evaluation grids. Additional updates improve documentation, add new suggested packages, and strengthen CI and coverage reporting.Enhancements to
gg_partial_rfsrcand Documentation:gg_partial_rfsrcfunction now automatically snaps requestedpartial.timevalues to the nearest availabletime.interestvalues in survival forests, preventing prediction errors and making the function more robust. It also adds new argumentspartial.timeandn_evalfor finer control, and uses quantile grids for continuous predictors to improve speed and smoothness. Documentation and Rd files are updated accordingly. [1] [2] [3] [4] [5] [6] [7] [8]Continuous Integration and Coverage Improvements:
lazyevalPREXPR removal), with steps to bootstraprcmdcheckand allow failures on R-devel without failing the whole workflow. [1] [2] [3] [4]codecov.ymlconfiguration file to enforce minimum code coverage thresholds (65% for main, 60% for PR patches) and configures reporting behavior.codecov.ymlin R builds by updating.Rbuildignore.Package Metadata and Documentation:
2.7.0.9001and the date, and addsknitrandplotlytoSuggestsinDESCRIPTION. [1] [2]_pkgdown.ymlto add new tutorial articles to the documentation site.Cleanup:
.claude/settings.local.jsonfile, cleaning up project configuration.This pull request adds several improvements and enhancements to thegg_partial_rfsrcfunction and its documentation, as well as minor updates to package metadata and CI workflow configuration. The most important changes are the addition of new arguments and logic to better handle survival forests and continuous variables, improved documentation, and updates to continuous integration for better R-devel compatibility.Enhancements to
gg_partial_rfsrc:partial.timeargument togg_partial_rfsrc, allowing users to specify desired time points for survival forests. Values are automatically snapped to the nearest availabletime.interestvalue to avoid errors inrandomForestSRC::partial.rfsrc. Default behavior now uses three quartile points oftime.interestifpartial.timeisNULL. [1] [2] [3] [4] [5] [6]n_evalargument to control the number of evaluation points for continuous predictors, improving performance by evaluating on a quantile grid instead of all observed values. [1] [2] [3] [4]Documentation improvements:
gg_partial_rfsrcto describe the new arguments, survival forest handling, and best practices for logical predictors. [1] [2] [3] [4]Continuous integration and metadata updates:
2.7.0.9001and date inDESCRIPTION. AddedknitrandplotlytoSuggests. [1] [2].claude/settings.local.jsonfile.