Package: ImpAdaptType2Censor
Type: Package
Title: Data Generation and Statistical Inference for Improved Adaptive
        Type-II Progressive Censoring Schemes
Version: 0.1.0
Authors@R: c(
    person("Shikhar", "Tyagi", email = "shikhar1093tyagi@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1606-0844")),
    person("Arvind", "Pandey", email = "arvindmzu@gmail.com", role = "aut"),
    person("Bhupendra", "Singh", email = "bhupendra.rana@gmail.com", role = "aut"),
    person("Vrijesh", "Tripathi", email = "vrijesh.tripathi@uwi.edu", role = "aut"))
Description: Comprehensive computational routines for random data
        generation, Maximum Likelihood Estimation (MLE), Maximum
        Product of Spacings Estimation (MPSE), and MCMC Bayesian
        estimation under the Improved Adaptive Type-II Progressive
        Censoring Scheme (IAT-II PCS). Users can supply custom
        probability density functions (PDF), cumulative distribution
        functions (CDF), survival functions, parameter ranges, and
        progressive censoring plans for any continuous univariate
        lifetime distribution, or rely on built-in parametric models
        (e.g., Generalized Exponential). Point estimation methods
        include MLE via optimization algorithms
        (Broyden-Fletcher-Goldfarb-Shanno (BFGS), Newton-Raphson (NR),
        Nelder-Mead (NM), Conjugate Gradients (CG), L-BFGS-B, Simulated
        Annealing (SANN), and Berndt-Hall-Hall-Hausman (BHHH)) and
        MPSE. Bayesian inference utilizes Metropolis-Hastings within
        Gibbs sampling under Squared Error Loss (SEL) and LINEX Loss
        (LL) functions to compute point estimates and Highest Posterior
        Density (HPD) credible intervals. Asymptotic confidence
        intervals for parameters, reliability, and hazard rate
        functions are constructed using asymptotic normality and delta
        method. Methods are based on Dev and Chacko (2026, Journal of
        the Iranian Statistical Society, 25, 1-29), Yan, Zhang, and
        Dong (2021, Journal of Computational and Applied Mathematics,
        381, 113022, <doi:10.1016/j.cam.2020.113022>), Ng, Kundu, and
        Chan (2004, Naval Research Logistics, 51, 1145-1168,
        <doi:10.1002/nav.20045>), Cheng and Amin (1983, Journal of the
        Royal Statistical Society Series B, 45, 394-403,
        <doi:10.1111/j.2517-6161.1983.tb01268.x>), Kundu and Gupta
        (1999, Australian & New Zealand Journal of Statistics, 41,
        173-188, <doi:10.1111/1467-842X.00072>), and Berndt, Hall,
        Hall, and Hausman (1974, Annals of Economic and Social
        Measurement, 3, 653-665).
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.3.3
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-07 11:20:24 UTC; root
Author: Shikhar Tyagi [aut, cre] (ORCID:
        <https://orcid.org/0000-0003-1606-0844>), Arvind Pandey [aut],
        Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: https://shikhartyagi.r-universe.dev
Date/Publication: 2026-08-07 15:30:02 UTC
RemoteUrl: https://github.com/cran/ImpAdaptType2Censor
RemoteRef: HEAD
RemoteSha: fbccdc2f6278c360b53ff76f0b4c5be541d61275
