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 Articles 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/. Title A name given to the resource Modelling Climate, COVID-19, and Reliability Data: A New Continuous Lifetime Model under Different Methods of Estimation Subject The topic of the resource Arvind distribution; Least squares estimation; Maximum likelihood estimation; Maximum product spac-ings; Stress strength reliability Description An account of the resource In this article, a new continuous probability distribution called Arvind distribution is developed and studied. The proposed distribution has only one parameter but it exhibits a wide variety of shapes for density and hazard rate functions. A number of important distributional properties including mode, quantile function, moments, skewness, kurtosis, mean deviation, probability-weighted moments, stress-strength reliability, order statistics, reliability and hazard rate functions, Bonferroni Lorenz and Zenga curves, conditional moments, mean residual and mean past life functions, and stochastic ordering of the Arvind distribution are derived. For point estimation of the parameter of the proposed distribution, six estimation procedures including maximum likelihood, maximum product spacings, least squares, weighted least squares, Cram-von Mises, and Anderson-Darling estimators are used. The interval estimation of the unknown parameter has also been discussed using observed Fishers information. A vast simulation study has been conducted to examine the behaviour of different estimation procedures. Finally, the applicability of the proposed model is demonstrated by using three real-life datasets. The results of the real data analysis clearly announce that the Arvind distribution can be a better alternative to several existing models for modelling different types of data from various fields. 2024, Society of Statistics, Computer and Applications. All rights reserved. Creator An entity primarily responsible for making the resource Pandey A.; Singh R.P.; Tyagi S.; Tyagi A. Source A related resource from which the described resource is derived Statistics and Applications, Vol-22, No. 2, pp. 1-27. Publisher An entity responsible for making the resource available Society of Statistics, Computer and Applications Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="" target="_blank" rel="noreferrer noopener"></a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209795525&amp;partnerID=40&amp;md5=327a5ff06a0475817af7810685ba795f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209795525&amp;partnerID=40&amp;md5=327a5ff06a0475817af7810685ba795f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 24547395 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Pandey A., Department of Statistics, Central University of Rajasthan, Rajasthan, 305817, India; Singh R.P., Department of Statistics, Central University of Rajasthan, Rajasthan, 305817, India; Tyagi S., Department of Statistics and Data Science, Christ deemed to be University, Bangalore, 560073, India; Tyagi A., Department of Statistics, Chaudhary Charan Singh University, Meerut, 250004, India