Changes in version 1.1 (2026-08-01)                   

New features

  - Added support for the Cox proportional hazards model via family =
    "cox". Feature screening for this family uses a new (iterative) sure
    independence screening routine driven by the extended BIC of the
    marginal Cox fits.

  - y may now be supplied for the Cox family either as a survival::Surv
    object or as a two-column (time, status) matrix or data frame.

  - Added a robust Median-of-Means gradient-descent (MoM-GD) estimator,
    selected with robust = "mom", for heavy-tailed responses. It
    supports the Gaussian and Negative-Binomial (family =
    "negative.binomial") families and reports basic bootstrap confidence
    intervals.

  - New arguments accompanying the robust estimator:
    
      - nblock — number of Median-of-Means blocks (default 5).
      - nboot — number of bootstrap resamples for the confidence
        interval (default 200).
      - theta — fixed Negative-Binomial dispersion; estimated from the
        screened design when NULL.

  - New argument CI controls whether confidence intervals are computed.
    The default depends on the estimator: TRUE for robust = "none"
    (closed-form intervals are cheap) and FALSE for robust = "mom" (the
    bootstrap is not run unless requested). When CI = FALSE, only point
    estimates are returned and the interval bounds are NA.

  - Added two example datasets: data_cox_model and data_nb_model.

Documentation

  - Expanded the documentation for mglm.test() to describe the accepted
    forms and constraints of every argument, and added runnable examples
    for the Cox model and for robust MoM estimation.

  - The package description no longer advertises p-values; the function
    reports information-gain point estimates and confidence intervals.

Dependencies

  - Removed the dependency on tidyverse, which was imported in full but
    not necessary. This considerably reduces the installation footprint.

  - Added explicit imports of stats::BIC(), stats::sd(), and
    survival::Surv().

  - Added testthat (>= 3.0.0) to Suggests and enabled testthat
    edition 3.

Bug fixes and improvements

  - Substantially expanded input validation with informative error
    messages. X, y, mod.idx, family, robust, penalty, tune, CI.type,
    iter, trace, conf.level, lambda, nlambda, nboot, nblock, and theta
    are all checked for type, shape, finiteness, and admissible ranges.
    mod.idx must now be a non-empty list of disjoint, in-range column
    indices.

  - Fixed the handling of a user-supplied lambda sequence or confidence
    levels.

                  Changes in version 1.0 (2025-09-03)                   

  - Initial release.

  - mglm.test() estimates the information gain contributed by individual
    modalities in multimodal regression models, measured by Expected
    Relative Entropy (ERE) or a pseudo-R-squared, with confidence
    intervals. Supports the Gaussian and Binomial families with
    canonical links.

  - summary() method for objects of class mglm.test.

  - Example datasets data_linear_model and data_logistic_model.