Package: GammaFrailty
Type: Package
Title: Gamma Frailty Regression Models with Multiple Baseline
        Distributions
Version: 0.1.0
Authors@R: person("Shikhar", "Tyagi",
    email = "shikhar1093tyagi@gmail.com",
    role = c("aut", "cre"),
    comment = c(ORCID = "0000-0003-1606-0844"))
Description: Implements univariate gamma frailty regression models for
    survival data with six different baseline distributions: the Arvind
    distribution (Pandey et al., 2024), the Lindley distribution
    (Lindley, 1958), the Linear Failure Rate distribution (Bain, 1974),
    the Power Xgamma distribution (Tyagi et al., 2022), the Modified
    Topp-Leone distribution (Singh et al., 2025), and the Power Failure
    Rate distribution (Mugdadi, 2005). The package supports uncensored
    (complete) and censored data (right, left, interval, and progressive
    censoring) with and without covariates. It provides maximum likelihood
    estimation, standard errors, confidence intervals, t-statistics,
    p-values, Akaike Information Criterion (AIC), Bayesian Information
    Criterion (BIC), a bootstrap approximation of the Widely Applicable
    Information Criterion (WAIC), k-fold cross-validation, variance
    inflation factors, R-squared, adjusted R-squared, Mean Squared Error
    (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), an
    overall model F-test, frailty variance estimation, survival
    probabilities at user-specified time points, median survival, expected
    survival within a fixed window, risk predictions, marginal
    predictions, martingale and deviance residuals, standardized and
    studentized residuals, leverage values, Cook's distance, Difference
    in Fits (DFFITS), Difference in Betas (DFBETAS), and a comprehensive
    suite of diagnostic and survival plots including Kaplan-Meier overlays
    and coefficient forest plots. Random number generation is available
    for each baseline distribution and the full frailty model, and a
    simulation study function evaluates parameter recovery across sample
    sizes and censoring scenarios.
    References are Lindley (1958) <doi:10.1111/j.2517-6161.1958.tb00278.x>,
    Mugdadi (2005) <doi:10.1016/j.amc.2004.09.064>,
    Bain (1974) <doi:10.1080/00401706.1974.10489237>,
    Singh, Tyagi, Singh, and Tyagi (2025)
    <https://ph02.tci-thaijo.org/index.php/thaistat/article/view/257215>,
    Pandey, Singh, Tyagi, and Tyagi (2024)
    <https://ssca.org.in/journal.html>, and
    Tyagi, Kumar, Pandey, Saha, and Bagariya (2022)
    <https://ijsreg.com/>.
License: GPL-3
Depends: R (>= 4.0.0)
Imports: survival, maxLik, numDeriv, MASS, stats, graphics, grDevices,
        utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-11 18:44:25 UTC; 30017827
Author: Shikhar Tyagi [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-1606-0844>)
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-18 17:00:02 UTC
