Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Gillariose, Jiju; Abdelwahab, Mahmoud M.; Elbatal, Ibrahim; Joseph, Joshin; Balogun, Oluwafemi Samson; Hasaballah, Mustafa M. Title A name given to the resource A New Versatile Discrete Distribution for Censored Data: Frequentist and Bayesian Methods With Real-Life Applications Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived IEEE Access;Volume;13;pp.196552-196564 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ACCESS.2025.3627766" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ACCESS.2025.3627766</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105020722018?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105020722018?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gillariose J., CHRIST (Deemed to be University), Department of Statistics and Data Science, Karnataka, Bengaluru, 560029, India; Abdelwahab M.M., Faculty of Science, Department of Mathematics and Statistics, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Elbatal I., Faculty of Science, Department of Mathematics and Statistics, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Joseph J., SCAPS, Marian College Kuttikkanam (Autonomous), Idukki, Kerala, Kuttikkanam, 685531, India; Balogun O.S., University of Eastern Finland, School of Computing, Kuopio, 70211, Finland; Hasaballah M.M., Marg Higher Institute of Engineering and Modern Technology, Department of Basic Sciences, Cairo, 11721, Egypt Description An account of the resource This study introduces a novel and highly flexible class of discrete probability distributions tailored to model the diverse monotonic failure-rate patterns frequently observed in stock-market data. The proposed distribution accommodates outliers effectively and serves as a discrete analogue of the exponential law, enabling analysts to derive robust and interpretable insights into market dynamics. Fundamental mathematical characteristics of the distributionsuch as the probability-generating function, mean, and varianceare thoroughly derived. The model is further extended to handle Type-II censored data, enhancing its applicability to real-world scenarios where incomplete observations are common. Parameter estimation is performed using both maximum-likelihood and Bayesian approaches, with a special focus on techniques suitable for censored samples. The performance and reliability of the estimators are examined through extensive simulation studies. To validate the practical utility of the model, it is applied to five real stock-market datasets obtained from Indiastat. The results demonstrate a superior empirical fit, affirming the models relevance in capturing the underlying patterns of financial time series. This distribution provides a valuable tool for analysts and researchers in the fields of financial statistics, risk modeling, and market behavior analysis. 2013 IEEE. Subject The topic of the resource Bayesian analysis; Discrete probability distributions; generalized distribution families; maximum likelihood estimation; simulation; stock market data; type-II censored data Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISSN: 21693536; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online