01 دی 1403
حسين حق بين

حسین حق بین

مرتبه علمی: استادیار
نشانی: دانشکده مهندسی سیستم های هوشمند و علوم داده - گروه آمار
تحصیلات: دکترای تخصصی / آمار
تلفن: 077322
دانشکده: دانشکده مهندسی سیستم های هوشمند و علوم داده

مشخصات پژوهش

عنوان The exponentiated odd log-logistic family of distributions: properties and applications
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
Generated family; Maximum likelihood; Moment; Odd log-logistic distribution; Probability weighted moment; Quantile function; Rényi entropy
مجله Journal of Statistical Modelling: Theory and Applications
شناسه DOI
پژوهشگران مراد علیزاده (نفر اول) ، سعید طهماسبی (نفر دوم) ، حسین حق بین (نفر سوم)

چکیده

Based on the generalized log-logistic family (Gleaton and Lynch (2006)) of distributions, we propose a new family of continuous distributions with two extra shape parameters called the exponentiated odd log-logistic family. It extends the class of exponentiated distributions, odd log-logistic family (Gleaton and Lynch (2006)) and any continuous distribution by adding two shape parameters. Some special cases of this family are discussed. We investigate the shapes of the density and hazard rate functions. The proposed family has also tractable properties such as various explicit expressions for the ordinary and incomplete moments, quantile and generating functions, probability weighted moments, Bonferroni and Lorenz curves, Shannon and Rényi entropies, extreme values and order statistics, which hold for any baseline model. The model parameters are estimated by maximum likelihood and the usefulness of the new family is illustrated by means of three real data sets