Changes in version 0.3.0 (2026-10-06)                  

Breaking changes

  - The latency component is now parametrized through the scale
    parameter lambda = exp(x %*% beta) for all distributions, as in an
    accelerated failure time model (the same convention as
    survival::survreg()). Previously, the exponential, Rayleigh, Weibull
    and log-normal distributions used a rate parametrization. The fitted
    model and the log-likelihood are unchanged, but the latency
    coefficients of these four distributions now have the opposite sign
    (and, for Weibull and Rayleigh, a different scale) relative to
    version 0.2.0. A positive coefficient now means longer survival for
    the uncured. The log-logistic and inverse Gaussian results are
    unchanged. rMCM(), residuals(), qqMCR() and plot() follow the new
    parametrization.
  - The liver dataset was replaced by the liver cancer data used in the
    accompanying paper (1,736 patients; covariates sex, age, medh, race,
    grade, chemo and radio).

Bug fixes

  - Standard errors of the latency coefficients for the log-normal
    distribution were too small; they are now correct.
  - summary() failed when the data had been modified after the fit (for
    example, when running the help-page examples).
  - rMCM() failed when x had a single covariate besides the intercept.
  - plot() no longer triggers the ggplot2 deprecation warning about
    size.
  - For the inverse Gaussian distribution, the starting values of the
    latency coefficients followed the old rate parametrization, which
    could make the EM algorithm stop at a degenerate solution for some
    models.

New features and improvements

  - summary() shows significance stars and a summary of the quantile
    residuals, and returns the coefficient tables as numeric matrices.
  - residuals() returns an object that prints the first residuals and a
    summary instead of every value.
  - MCRfit() warns when the EM algorithm does not converge within maxit
    iterations and stores a logical convergence element; summary()
    reports it.
  - print() and summary() show the link function (with tau only for the
    power links), label the incidence coefficients consistently as the
    "Uncured part", show the shape parameter only when it is estimated,
    and return their argument invisibly.
  - Documentation of MCRfit(), rMCM() and plot() was corrected and
    expanded.
  - knitr is no longer a dependency.