Changes in version 0.1.0 (2026-08-23)                  

Bug fixes

  - nnmaxheap_C(), the projection onto non-negative, non-increasing
    vectors, returned wrong values in the 0.1.0 release (#12, reported
    by @D4EM3ON). Any single-element block overwrote the first value of
    the next block, and a negative final value was not clipped at 0. For
    example, nnmaxheap_C(c(5, 3, 3, 1)) returned 5 5 5 1 instead of
    5 3 3 1, and nnmaxheap_C(c(3, 1, 2, -1)) returned 3 3 3 -1 instead
    of 3 1.5 1.5 0. The output was still non-increasing, but its values
    were inflated, so this changes numerical results wherever the
    projection is applied: predict() on survival fits (survival = TRUE)
    and the scores used by cv_orthoMTL(survival = TRUE), hence its model
    selection. Regression and classification fits are not affected.
    Results produced with 0.1.0 on survival data should be recomputed.
    The projection used in the earlier internal versions of the code
    behind the published analyses was correct and is not affected. The
    function is now tested against an isotonic-regression oracle
    (stats::isoreg).

Renamed from orthopen to orthoMTL

This release represents a major refactor and scope expansion of the
orthopen package (https://github.com/kevinVervier/orthopen).

New features

  - Survival analysis mode: survival and censored.mat arguments in
    orthoMTL() enable censored time-to-event data.
  - Elastic-net sparsity: alpha mixing parameter in [0, 1] blending the
    orthogonality penalty (alpha = 0) with L1/Lasso (alpha = 1).
  - Survival data utilities: create_longitudinal_labels(),
    create_indicator_matrix(), create_constraint_matrix().
  - Cross-validation: cv_orthoMTL() with parallel grid search over
    lambda, step size, diagonal value, and elastic-net mixing.
  - Bootstrap inference: bootstrap_orthoMTL() compares real coefficient
    variability against null-model permutations.
  - Evaluation: cindex_mtl() for multi-task concordance index.
  - Visualisation suite: plot_heatmap(), plot_correlation(),
    plot_prediction(), plot_bootstrap().

Breaking changes from orthopen

  - Function renamed: orthopen() → orthoMTL().
  - Return list key renamed: $W → $B.
  - Default disjoint changed from TRUE to FALSE.
  - Elastic-net is controlled by a single alpha mixing parameter in
    [0, 1] (replacing the enet/lambda1 pair). The penalty is lambda *
    [(1-alpha)/2 * Omega_K(W)^2 + alpha * ||W||_1], ported from orthopen
    v1.1.0. This fixes the previous inconsistent mixing (L2 ≈ 0.25lambda
    vs L1 = 0.5lambda1).
  - Iso package dependency removed; replaced by internal nnmaxheap_C().

Bug fixes

  - Variable T (masking base::TRUE) renamed to numTasks.
  - Input validation added for X, Y, lambda, alpha.
  - Warning emitted when max_iter is reached without convergence.
  - Logistic gradient corrected for labels in {-1, +1} (ported from
    orthopen v1.1.0): the gradient previously used the {0, 1}
    cross-entropy form, which is wrong for y = -1.
  - Logistic loss made overflow-safe via the stable softplus identity
    max(-z,0) + log1p(exp(-|z|)) and exponent clipping in the gradient.

Infrastructure

  - Package scaffolding: LICENSE (GPL-3), testthat runner,
    inst/CITATION, GitHub Actions CI.
  - Selective NAMESPACE exports.

General-purpose regression & classification support

The solver already supported regression (logistic = FALSE, survival =
FALSE) and classification (logistic = TRUE); these are now first-class
end-to-end with matching evaluation, tuning, and simulation scaffolding
(previously survival-only):

  - Non-survival metrics: rmse_mtl(), r2_mtl() (regression) and
    accuracy_mtl(), auc_mtl() (classification), complementing the
    survival cindex_mtl() (unchanged).
  - Mode-aware cross-validation: cv_orthoMTL() gains logistic and metric
    arguments. The scoring metric now defaults by mode — cindex for
    survival, auc for logistic, rmse otherwise — and selection honours
    each metric's optimisation direction.
  - predict() type argument: "link" (default, unchanged), "response"
    (sigmoid probabilities for logistic fits), and "class" (predicted
    {-1, +1} labels for logistic fits).
  - Simulation modes: simulate_mtl(mode = ...) now generates
    "regression" and "classification" responses in addition to
    "survival" (the default).

Solver

  - Gradient-step schedule exposed (schedule argument to orthoMTL()).
    The previously hardcoded sqrt(i) decay is now schedule = "sqrt" (the
    default, reproducing prior results exactly); "log", "const", and
    "linear" are also available. An A/B study
    (validation/ab_s02_gradient_schedule.R) found "log"/"const" reach
    the same optimum ~12--17x faster than "sqrt", while "linear" can
    stall. Changing the schedule changes the optimisation path and the
    exact coefficients, so the default is unchanged. cv_orthoMTL() and
    bootstrap_orthoMTL() gained a matching schedule argument (passed to
    every fit), so grid search and bootstrap can use the faster
    schedules too.

Behaviour change

  - cv_orthoMTL(survival = FALSE) previously scored every fold with the
    survival C-index regardless of the data; it now defaults to RMSE for
    plain regression (and AUC when logistic = TRUE). Pass metric =
    "cindex" to restore the old scoring.

                        Changes in version 0.0.1                        

  - Initial release on GitHub.
  - Core solver for regression and classification with orthogonal column
    constraints and disjoint support constraints.
  - Two vignettes reproducing Figures 2 and 3 from Vervier et al. (2014,
    ECML-PKDD).