Discrete Modified Lindley Distribution for Censored Data

This article goes into more detail about the discrete modified Lindley distribution from Tomy et al. (Bull. Comput. Appl. Math. (Bull CompAma), 10(1): 11-32, 2022) in terms of statistical inference process that includes censoring. The benefit of using this particular variant of the discrete distribution is that it may be applied to data sets that are unimodal, increasing, decreasing, or positively skewed. This article uses both frequentist and Bayesian methods to present inferences about the distribution. Additionally, a cure fraction is also incorporated into the model. The traditional goodness-of-fit measure approach is used to evaluate the parameters of the distribution. Real-world survival data of COVID-19 patients and patients with pelvic tumours are used to illustrate the procedure. When compared to alternative one-parameter discrete competitive statistical models, the results of the study on an applicational level imply that the model based on the modified Lindley distribution performs well.