 The logistic-X family of distributions and its applicationsM. H. Tahir, Gauss M. Cordeiro, Ayman Alzaatreh, M. Mansoor and M. Zubair Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 24, 7326-7349 Abstract: The logistic distribution has a prominent role in the theory and practice of statistics. We introduce a new family of continuous distributions generated from a logistic random variable called the logistic-X family. Its density function can be symmetrical, left-skewed, right-skewed, and reversed-J shaped, and can have increasing, decreasing, bathtub, and upside-down bathtub hazard rates shaped. Further, it can be expressed as a linear combination of exponentiated densities based on the same baseline distribution. We derive explicit expressions for the ordinary and incomplete moments, quantile and generating functions, Bonferroni and Lorenz curves, Shannon entropy, and order statistics. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. We also investigate the properties of one special model, the logistic-Fréchet distribution, and illustrate its importance by means of two applications to real data sets. Date: 2016 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:45:y:2016:i:24:p:7326-7349 Ordering information: This journal article can be ordered from DOI: 10.1080/03610926.2014.980516 Access Statistics for this article Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals |
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