Package: gofPHCS 0.1.0

gofPHCS: Goodness-of-Fit Tests for Complete, Progressively Type-II, Type-I Hybrid, and Type-II Hybrid Censored Data

Provides goodness-of-fit tests for lifetime data collected under complete sampling, progressive Type-II censoring, and Type-I/Type-II hybrid censoring schemes. Users supply the observed (censored) data and the assumed probability density/mass function, cumulative distribution function, or survival function of the target model, and the package returns the corresponding test statistic together with an asymptotic or Monte Carlo p-value. Implements the spacings-based exponentiality test of Balakrishnan, Ng and Kannan (2002, in "Goodness-of-Fit Tests and Model Validity", Birkhauser, pp. 89-111) and its location-scale generalization Balakrishnan, Ng and Kannan (2004) <doi:10.1109/TR.2004.833317>, the power comparison and Kaplan-Meier based tests of Doering and Cramer (2019) <doi:10.1080/00949655.2019.1648468>, the Kolmogorov-Smirnov type tests for hybrid censored data of Banerjee and Pradhan (2018) <doi:10.1080/03610926.2016.1205616>, and follows the unified treatment of hybrid censoring schemes reviewed in Balakrishnan and Kundu (2013) <doi:10.1016/j.csda.2012.03.025> and in Cramer and Balakrishnan (2023, "Hybrid Censoring Know-How", Chapter 11) <doi:10.1016/B978-0-12-398387-9.00019-2>.

Authors:Shikhar Tyagi [aut, cre], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]