NEWS

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bigPLScox 0.8.1 (2025-11-18)

• Fix links in the DESCRIPTION files.

bigPLScox 0.8.0

• Added DOI of the package.

• Added high performance PLS Cox backends:

  • big_pls_cox_fast() for exact PLS Cox fits on both dense matrices and bigmemory::big.matrix objects.
  • big_pls_cox_gd() for gradient based optimisation of Cox partial likelihood in the latent PLS space.

• big_pls_cox_gd() now supports several optimisation schemes via the method argument:

  • "gd" for a basic fixed step gradient descent,
  • "bb" for a Barzilai Borwein step size,
  • "nesterov" for Nesterov style acceleration,
  • "bfgs" for a quasi Newton update.

  All optimisers share the same PLS scores and differ only in how the Cox coefficients are updated.

bigPLScox 0.7.0

• Fixed problem in C code that led to an additional error during CRAN tests.

• Added helpers for big_pls_cox() and big_pls_cox_gd().

• New prediction helpers:

  • predict.big_pls_cox_fast() and predict.big_pls_cox_gd() now handle dense matrices, big.matrix inputs and in-sample prediction.
  • type = "components" returns the PLS scores for the requested components.
  • Arguments comps and coef allow partial use of components and user supplied Cox coefficients.

• Added simple diagnostic accessors for gradient based fits, including iteration counts, log-likelihood trajectory, gradient norms and step sizes.

bigPLScox 0.6.0 (2025-11-11)

See the "Release highlights" section of the README for a condensed overview of these changes.

• Added C++ implementations for Cox deviance residuals with streaming support for bigmemory matrices together with benchmarking utilities.
• Introduced prediction wrappers and component selection helpers (AIC/BIC) for big_pls_cox() and big_pls_cox_gd().
• Enabled naive sparsity control in big_pls_cox() and exposed survival model objects for downstream predictions.
• Added cross-validation helpers cv.big_pls_cox() and cv.big_pls_cox_gd() mirroring the plsRcox criteria, including the recommended survivalROC iAUC metric by default.
• Documented the legacy and big-memory prediction helpers with runnable examples and cross references to diagnostic utilities.
• Extended unit test coverage for the new deviance and prediction features.
• Fixed cv.coxgpls() to accept big.matrix predictors without coercion errors.

bigPLScox 0.5.0

• Added reproducible benchmarking utilities under inst/benchmarks comparing big_pls_cox() against plsRcox::plsRcox() on in-memory and file-backed matrices.
• Published two package vignettes covering introductory workflows and large-scale analyses with bigmemory.
• Added an introductory vignette covering the core Cox-PLS workflow.
• Refreshed the README and website copy to highlight core functionality and to demonstrate working examples without warnings, including guidance on learning materials and benchmarking resources.
• Completed package-level documentation with bibliographic references.
• Updated package metadata to list optional dependencies used in docs and benchmarks.

bigPLScox 0.4.0

• Updated maintainer contact details in DESCRIPTION.
• Added unit tests for big_pls_cox() and big_pls_cox_gd() stability checks.
• Added unit tests covering the new C++-accelerated Cox PLS implementation and cross-validation utilities.

bigPLScox 0.3.0

• Improved big_pls_cox() numerical stability and added support for additional convergence diagnostics in the gradient-descent solver.
• Refactored stochastic gradient solvers to better integrate with bigmemory file-backed matrices.
• Improved numerical stability of the deviance residual computations.

bigPLScox 0.2.0

• Expanded documentation examples for deviance residuals and Cox model utilities.
• Added dataset documentation for micro.censure and simulated Cox examples.
• Added pkgdown site configuration and continuous integration workflows.

bigPLScox 0.1.0

• Introduced gPLS and sgPLS model families with support for grouped predictors and deviance residual pipelines with cross-validation support.

bigPLScox 0.0.1

• Initial package skeleton with core data objects and helper routines.