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selSurv 0.1.1

Initial CRAN release.

• Updated the simulation-study reference to the published journal DOI.
• Clarified public method descriptions and documentation.
• Simplified the README while retaining development smoke tests.

selSurv 0.1.0

Initial public GitHub release.

• Provides Cox-Lasso screening, support-restricted Cox refitting, split-sample inference, approximately debiased coefficient estimates, and score-level and model-based bootstrap workflows.
• Supports fixed-support inference and procedure-level re-selection, with explicit distinctions between the corresponding inferential targets.
• Corrects the Cox score and observed information calculations for tied event times under the Breslow and Efron conventions.
• Includes numerical regression tests against an independent Cox partial-likelihood reference implementation.
• Documents the supported Lasso penalty scope and the conventions used for fitting, refitting, and bootstrap inference.

selSurv 0.1.0.9016

• Clarified the supported penalty scope of the inferential workflows. coxlasso_fit() continues to expose the glmnet elastic-net mixing parameter for fitting flexibility, while the inferential validation in selSurv currently concerns Lasso screening (alpha = 1).
• Restricted coxlasso_debias() and the associated wild and Efron score-bootstrap backends to Cox-Lasso pilots with alpha = 1; non-Lasso pilots now fail explicitly rather than returning apparently validated debiased inference.
• Kept split-sample, fixed-support model-based bootstrap, and procedure-level re-selection workflows computationally available for non-Lasso mixing parameters, but added explicit warnings that these settings have not been separately validated inferentially in selSurv.
• Added a package workflow guide documenting inferential targets, bootstrap interfaces, penalty-parameter naming, penalty scope, and tie-handling distinctions.
• Added focused regression tests for Lasso-only debiasing safeguards and non-Lasso warning behavior.

selSurv 0.1.0.9015

• Made Cox tie conventions explicit across the model-based bootstrap workflows: penalized Cox-Lasso selection uses the Breslow convention, ordinary post-selection Cox refits use Efron’s method, and model-based event generation uses an explicit Breslow cumulative baseline hazard.
• Added compatibility handling for installed glmnet versions that do not formally support cox.ties, avoiding silently ignored tie arguments while preserving the historical Breslow selection convention.
• Made the Cox-Lasso cross-validation convention explicit as deviance loss with grouped cross-validation, while retaining CV-min, 10 folds, and Lasso mixing alpha = 1 as the general fitting defaults.
• Updated the general re-selection defaults to conf_level = 0.95, seed = NULL, and standardize = TRUE. A randomly generated root seed is stored when seed = NULL, after which bootstrap-generation and CV streams remain deterministic and method-order invariant.
• Retained rng_mode = "legacy_nki70" and its historical Breslow, random-stream, solver-tolerance, and standardization conventions solely for exact reproduction of the archived NKI70 analysis.
• Revised coxlasso_split() to separate interval confidence through conf_level = 0.95 from Cox-Lasso mixing through penalty_alpha = 1. Historical alpha calls remain supported as a deprecated confidence-level bridge.
• Kept the historical direct bootstrap backend defaults unchanged for compatibility; the unified coxlasso_boot() interface remains the recommended bootstrap entry point with B = 500, conf_level = 0.95, and seed = NULL.
• Added regression tests for tie handling, Breslow baseline generation, cross-validation conventions, re-selection seed semantics, general-purpose defaults, and split-sample compatibility.

selSurv 0.1.0.9014

• Standardized categorical data-frame inputs to stable treatment coding: factors, ordered factors, character variables, and logical variables now contribute (k-1) design-matrix coordinates using the first level as the reference, independent of data-frame column order.
• Ordered factors are treated as ordinary categorical predictors rather than using polynomial contrasts; logical predictors use FALSE as the reference level. Numeric and integer covariates remain numeric.
• Character predictors are converted to unordered factors. Users who require a particular reference category should supply a factor with an explicit level order or use relevel() before fitting.
• Selection and re-selection continue to operate on individual design-matrix coordinates, not on whole categorical variables as groups. Consequently, Lasso selection can depend on the chosen reference level.
• Added explicit checks for constant categorical predictors, unsupported data-frame column classes, empty inputs, missing or non-finite values, invalid or duplicated design-column names, and generated dummy-name collisions.
• Added design-coordinate checks so that post-selection refits and externally supplied original workflows cannot silently use reordered or differently coded covariates.
• Expanded regression tests for factor, ordered-factor, character, logical, numeric, sparse-matrix, reference-level, contrast-option, input-boundary, and procedure-level re-selection behavior.

selSurv 0.1.0.9013

• Centralized covariate design-matrix normalization across the main Cox-Lasso workflow and procedure-level re-selection.
• coxlasso_boot_reselect() now accepts data-frame covariates using the same model.matrix(~ . - 1) expansion already used by coxlasso_fit(), including factor and logical columns.
• Added explicit rejection of missing and non-finite covariate values before model fitting.
• Added regression tests for numeric, factor/logical data-frame, and sparse-matrix inputs.
• Preserved the existing coding convention, numerical behavior, and archived NKI70 re-selection parity.

selSurv 0.1.0.9012

• Added an experimental procedure-level model-based bootstrap with Cox-Lasso re-selection through coxlasso_boot_reselect().
• Added fixed-support, fixed-penalty re-selection, bootstrap CV-min, CV-1SE, and AIC tuning variants.
• Non-selected coordinates are recorded as zero; failed non-empty unpenalized Cox refits remain missing rather than being converted to zero.
• Added method-level diagnostics for support overlap, model size, selection/refit success, tuning parameters, and coordinate-level re-selection frequencies.
• Added method-order-invariant random streams for normal use.
• Added rng_mode = "legacy_nki70" solely for reproducibility of the archived NKI70 analysis. The B=20 regression gate reproduces the archived support diagnostics, including the historical AIC refit failure pattern.
• The existing coxlasso_boot(inference = "conditional") semantics remain fixed-support and are not broadened to include procedure-level re-selection.

selSurv 0.1.0.9011

• Integrated the August 2026 unified coxlasso_boot() API with the recovered v12 package source.
• Added dispatch between debiased wild bootstrap and Efron’s bootstrap and fixed-support model-based bootstrap.
• Added compatibility with the established v12 selSurv_debias class.
• Kept procedure-level re-selection outside the first unified bootstrap API; re-selection remains available through coxlasso_boot_parametric().
• Added validation/dispatch tests and development use-case documentation.
• Archived the historical selSurv IWSM text as an unpublished draft and noted that the retained IWSM 2026 proceedings contribution was the PoSI work.
• Removed local .RData/.Rhistory workspace artifacts from the source tree.

selSurv 0.1.0.9000

Initial research implementation.

• Added Cox-Lasso fitting workflow.
• Added support-restricted Cox refitting.
• Added approximate debiasing workflow.
• Added multiplier wild and event-level score bootstraps.
• Added model-based bootstrap with fixed-support, fixed-lambda re-selection, and retuned re-selection modes.
• Added split-sample workflow.
• Added target and method summary helpers.
• Added vignette explaining target definitions and workflow interpretation.

selSurv 0.1.0.9001

• Added user-facing coef and se fields to coxlasso_fit() and coxlasso_refit() outputs.
• Added support-specific coef_support and se_support fields to coxlasso_refit().

selSurv 0.1.0.9002

• Added documentation for S3 print methods.
• Rewrote workflow Rd usage/argument documentation.
• Moved local smoke-test examples and implementation notes under inst/.
• Reduced R CMD check warnings/notes caused by package documentation layout.

selSurv 0.1.0.9003

• Fixed Rd code/documentation mismatches for coxlasso_wildboot() and coxlasso_efron_events().
• Added .Rbuildignore entries for stale top-level example/development files.
• Shortened the coxlasso_fit() Rd usage block.

selSurv 0.1.0.9004

• Added explicit roxygen usage block for coxlasso_fit() to remove Rd line-width NOTE.
• Broke the coxlasso_fit() function signature across lines.
• Removed empty inst/extdata from the source tree.

selSurv 0.1.0.9005

• Removed the obsolete combined coxlasso_workflows.Rd file to avoid duplicate Rd aliases after roxygen generates individual workflow documentation.
• Removed the manual coxlasso_fit.Rd file so roxygen can regenerate it from the explicit multi-line @usage block.

selSurv 0.1.0.9006

• Added plot_selection_diagnostics() for base-R visualization of re-selection and zero-frequency diagnostics.
• Added tests for diagnostic comparison and plotting helpers.

selSurv 0.1.0.9007

• Improved plot_selection_diagnostics() layout; default legend is now a compact top legend and neutral greys are used by default.

selSurv 0.1.0.9008

• Added a prettier default Cleveland-style dot plot to plot_selection_diagnostics().
• Kept grouped bars available via plot_type = "bar".
• Improved plot readability for many variables and small RStudio plot panes.

selSurv 0.1.0.9009

• Added a colorblind-friendly color palette to plot_selection_diagnostics().
• Added a robust legend_position = "side" default using a separate legend panel.
• Kept grouped bars available and improved the color bar plot option.

selSurv 0.1.0.9010

• Replaced the default side legend by a top legend panel in plot_selection_diagnostics().
• This avoids legend clipping in the RStudio zoom window and keeps the main plot area readable.

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.
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