predHCS: Point and Interval Prediction for Censored Data under Various
Hybrid Censoring Schemes
Implements generalized statistical point prediction and prediction
intervals for future failure times under various hybrid censoring schemes.
Supported censoring schemes include Type-I, Type-II, Generalized Type-I,
Generalized Type-II, Unified, Progressive Type-I, and Progressive Type-II
hybrid censoring schemes. Available prediction methods include Best Unbiased
Predictor (BUP), Conditional Median Predictor (CMP), Maximum Likelihood
Predictor (MLP), equal-tailed classical prediction intervals, Highest
Conditional Density (HCD) prediction intervals, and Bayesian prediction
intervals. Algorithms accept user-defined continuous probability density
functions, cumulative distribution functions, quantile functions, or survival
functions along with estimated parameter values. Methodological foundations
are based on Balakrishnan, Cramer, and Kundu (2023, ISBN:978-0123983879),
Shafay and Balakrishnan (2012) <doi:10.1080/03610918.2011.579367> for Type-I
hybrid censoring, Balakrishnan and Shafay (2012)
<doi:10.1080/03610926.2010.543300> for Type-II hybrid censoring, Shafay
(2017) <doi:10.1080/03610926.2016.1200093> for Generalized Type-I hybrid
censoring, Shafay (2016) <doi:10.1080/00949655.2015.1096361> for Generalized
Type-II hybrid censoring, Mohie El-Din, Nagy, and Shafay (2017)
<doi:10.18576/jsap/060113> for Unified hybrid censoring, Ebrahimi (1992)
<doi:10.1109/24.126685>, Valiollahi, Asgharzadeh, and Kundu (2017)
<doi:10.1214/15-BJPS302>, and Asgharzadeh, Valiollahi, and Kundu (2015)
<doi:10.1080/00949655.2013.848451>.
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[aut, cre],
Arvind Pandey [aut],
Bhupendra Singh [aut],
Vrijesh Tripathi [aut]