Provides generalized functions to compute Maximum Likelihood
    Estimation (MLE) for any univariate distribution under various censoring
    and truncation schemes.  Users supply the probability density function
    (PDF), cumulative distribution function (CDF), survival function, support
    bounds, and initial parameter values; the package constructs and maximizes
    the appropriate log-likelihood automatically.  Supported schemes include
    right and left truncation, random, right, left, interval, and middle
    censoring, block random censoring, balanced joint progressive Type-II
    (BJPT-II), progressive first failure, joint Type-I, Type-I, Type-II,
    progressive Type-II, Type-II progressively hybrid, joint Type-II, hybrid,
    hybrid Type-I, doubly Type-II, Type-I hybrid, and hybrid Type-II
    censoring.  Optimization methods include Newton-Raphson (NR),
    Broyden-Fletcher-Goldfarb-Shanno (BFGS), the BFGS algorithm implemented
    in R (BFGSR), Berndt-Hall-Hall-Hausman (BHHH), Simulated Annealing
    (SANN), Conjugate Gradients (CG), and Nelder-Mead (NM).  Inference
    summaries provide the Akaike Information Criterion (AIC), estimated
    coefficients, log-likelihood, iteration count, standard errors,
    z-values, p-values, and the variance-covariance matrix.  Methods are
    described in
    Nagar, Kumar, and Krishna (2026) <doi:10.59467/IJASS.2026.22.1>,
    Goel, Kumar, and Krishna (2026, "Estimation in power Lindley
    distributions using balanced joint progressively Type-II censored data"),
    Wu and Kus (2009) <doi:10.1016/j.csda.2009.03.010>,
    Goel and Krishna (2026) <doi:10.1007/s13198-026-03208-w>,
    Balakrishnan and Aggarwala (2000, ISBN:978-1-4612-1334-5),
    Mondal and Kundu (2020) <doi:10.1080/03610926.2018.1554128>,
    Ding and Gui (2023) <doi:10.3390/math11092003>,
    Prajapati, Mitra, and Kundu (2019) <doi:10.1007/s13571-018-0167-0>,
    Yadav, Jaiswal, and Yadav (2026) <doi:10.1007/s11135-026-02647-8>,
    Iyer, Jammalamadaka, and Kundu (2008) <doi:10.1016/j.jspi.2007.03.062>,
    Banerjee and Kundu (2008) <doi:10.1109/TR.2008.916890>,
    Kundu and Joarder (2006) <doi:10.1016/j.csda.2005.05.002>,
    Berndt, Hall, Hall, and Hausman (1974) "Estimation and Inference in
    Nonlinear Structural Models" <doi:10.3386/t0003>,
    Fletcher (1987, "Practical Methods of Optimization",
    ISBN:978-0-471-91547-8),
    Nelder and Mead (1965) <doi:10.1093/comjnl/7.4.308>,
    McKinnon (1999) "Convergence of the Nelder-Mead simplex method to a
    non-stationary point" <doi:10.1137/S1052623496303482>,
    Kirkpatrick, Gelatt, and Vecchi (1983) <doi:10.1126/science.220.4598.671>,
    Fletcher and Reeves (1964) <doi:10.1093/comjnl/7.2.149>, and
    Nocedal and Wright (2006, "Numerical Optimization",
    ISBN:978-0-387-30303-1).