Changes in version 0.1.0 (2026-10-21)                  

First release.

Models

  - BvCh — Marshall-Olkin type Bivariate Chen distribution. Probability
    density (dbvch), survival function (sbvch), hazard function (hbvch)
    and random generation (rbvch), plus the two components of the
    mixture representation (dbvch_ac, dbvch_sing).
  - BEC — Bivariate Extended Chen distribution: dbec, sbec, hbec, rbec,
    and the componentwise hazard gradients hbec1 and hbec2.
  - IFGM-Chen — Bivariate Inverse FGM Chen distribution built from the
    Inverse FGM copula and Chen marginals: relifgmchen, difgmchen,
    hifgmchen, rifgmchen, together with the copula itself (cifgm,
    cifgmdens, rifgm) and its dependence measures (tau_ifgm, rho_ifgm).

Univariate building blocks

  - Univariate Chen density, distribution, quantile, survival, hazard,
    hazard-rate-average, conditional reliability and random generation
    are taken from reliaR rather than re-implemented.
  - The univariate Extended Chen distribution, which reliaR does not
    provide, is implemented here (sech, hech, dech, pech, qech, rech).

Estimation, comparison and graphics

  - Maximum likelihood estimation: fitbvch, fitbec, fitifgmchen, with
    standard errors from the numerical Hessian, and logLik_bvch,
    logLik_bec, logLik_ifgmchen exported for direct use.
  - compare_models tabulates −log L, AIC and BIC; ksfit_bvch performs
    Kolmogorov-Smirnov goodness-of-fit tests for the three marginals.
  - Base-graphics surface and contour plots: plot_surface_bvch,
    plot_surface_bec, plot_reliability_ifgmchen, plot_contour_bvch.

Notes

  - BvCh::rchen draws reliaR::qchen(runif(n), beta, lambda) rather than
    calling reliaR::rchen, because in reliaR 0.2 that function disagrees
    with the package's own distribution function (Kolmogorov-Smirnov
    distance about 0.38 at beta = 1.5, lambda = 2, growing to about 0.85
    at beta = 2.5, and correct only when beta = 1). See ?chen.
  - hbvch implements the hazard as f/S; on the diagonal this reproduces
    the source formula h0(z) = alpha3 * beta * z^(beta-1) * exp(z^beta)
    exactly.
  - With the Inverse FGM copula formula as written in the source
    document, tau_ifgm and rho_ifgm are non-positive for gamma, omega
    >= 0 (tau = -0.0699, rho = -0.1049 at gamma = 0.6, omega = 0.4). The
    source document quotes a positive tau = 0.156 for the same
    parameters, which is inconsistent with the copula it also quotes.
    The formula has been implemented as given; see ?cifgm.