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.