MleCensoR: Maximum Likelihood Estimation under Censoring Schemes
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).
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[aut, cre],
Vrijesh Tripathi [aut]