CompRiskRel: Reliability and Competing Risks Analysis under Hybrid Censoring
Generalized computational algorithms for competing risks analysis,
stress-strength reliability modeling, optimal designs, and reliability
acceptance sampling plans under various hybrid censoring schemes. Includes
data generation routines, Maximum Likelihood Estimation (MLE) with seven
optimization algorithms ('Newton-Raphson', 'BFGS', 'BFGSR', 'BHHH', 'SANN',
'CG', and 'Nelder-Mead'), Bayesian inference via Gibbs sampling and
Metropolis-Hastings MCMC, Importance Sampling, and 'Lindley' asymptotic
approximation. Visualization functions generate histograms, dot plots,
and autocorrelation plots for model validation. Methodology and design
principles are based on 'Balakrishnan', 'Cramer', and 'Kundu' (2023,
"Hybrid Censoring Know-How: Designs and Implementations", Academic Press,
ISBN:978-0-12-398387-9).
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