Libby-Novick Kumaraswamy Distribution with Its Properties and Applications

The Kumaraswamy distribution is one of the most popular probability distributions with applications to real life data. In this paper, an extension of this distribution called the Libby-Novick Kumaraswamy (LNK) distribution is presented which is believed to provide greater flexibility to model scenar...

Full description

Bibliographic Details
Main Authors: Abdul Saboor, Zafar Iqbal, Muhammad Hanif, Munir Ahmad
Format: Article
Language:English
Published: Etamaths Publishing 2021-04-01
Series:International Journal of Analysis and Applications
Online Access:http://etamaths.com/index.php/ijaa/article/view/2236
id doaj-5882bd0450bb408ca86a93f531467043
record_format Article
spelling doaj-5882bd0450bb408ca86a93f5314670432021-08-26T13:44:41ZengEtamaths PublishingInternational Journal of Analysis and Applications2291-86392021-04-01193405439529Libby-Novick Kumaraswamy Distribution with Its Properties and ApplicationsAbdul Saboor0Zafar IqbalMuhammad HanifMunir AhmadNational College of Business Administration & Economics Lahore, PakistanThe Kumaraswamy distribution is one of the most popular probability distributions with applications to real life data. In this paper, an extension of this distribution called the Libby-Novick Kumaraswamy (LNK) distribution is presented which is believed to provide greater flexibility to model scenarios involving skew-normal data than original one. Analytical expressions for various mathematical properties including its cdf, quantile function, moments, factorial moments, conditional momennts, moment generating function, characteristic function, vitality function, information generating function, reliability measures, mean deviations, mean residual function, Bonferroni and Lorenz Curves are derived.The parameters’ estimation of LNK distribution is undertaken using the method of maximum likelihood estimation. A simulation study for different values of sample sizes, to assess the performance of the parameters of LNK distribution is provided.  For illustration and performance evaluation of LNK distribution three real-life data sets from the field of engineering and science adapted from earlier studies are used. On comparing the results to previously used methods, LNK distribution shows that it can give consistently better fit than other existing important lifetime models. It is found that the LNK distribution is more suitable and useful to study lifetime data.http://etamaths.com/index.php/ijaa/article/view/2236
collection DOAJ
language English
format Article
sources DOAJ
author Abdul Saboor
Zafar Iqbal
Muhammad Hanif
Munir Ahmad
spellingShingle Abdul Saboor
Zafar Iqbal
Muhammad Hanif
Munir Ahmad
Libby-Novick Kumaraswamy Distribution with Its Properties and Applications
International Journal of Analysis and Applications
author_facet Abdul Saboor
Zafar Iqbal
Muhammad Hanif
Munir Ahmad
author_sort Abdul Saboor
title Libby-Novick Kumaraswamy Distribution with Its Properties and Applications
title_short Libby-Novick Kumaraswamy Distribution with Its Properties and Applications
title_full Libby-Novick Kumaraswamy Distribution with Its Properties and Applications
title_fullStr Libby-Novick Kumaraswamy Distribution with Its Properties and Applications
title_full_unstemmed Libby-Novick Kumaraswamy Distribution with Its Properties and Applications
title_sort libby-novick kumaraswamy distribution with its properties and applications
publisher Etamaths Publishing
series International Journal of Analysis and Applications
issn 2291-8639
publishDate 2021-04-01
description The Kumaraswamy distribution is one of the most popular probability distributions with applications to real life data. In this paper, an extension of this distribution called the Libby-Novick Kumaraswamy (LNK) distribution is presented which is believed to provide greater flexibility to model scenarios involving skew-normal data than original one. Analytical expressions for various mathematical properties including its cdf, quantile function, moments, factorial moments, conditional momennts, moment generating function, characteristic function, vitality function, information generating function, reliability measures, mean deviations, mean residual function, Bonferroni and Lorenz Curves are derived.The parameters’ estimation of LNK distribution is undertaken using the method of maximum likelihood estimation. A simulation study for different values of sample sizes, to assess the performance of the parameters of LNK distribution is provided.  For illustration and performance evaluation of LNK distribution three real-life data sets from the field of engineering and science adapted from earlier studies are used. On comparing the results to previously used methods, LNK distribution shows that it can give consistently better fit than other existing important lifetime models. It is found that the LNK distribution is more suitable and useful to study lifetime data.
url http://etamaths.com/index.php/ijaa/article/view/2236
work_keys_str_mv AT abdulsaboor libbynovickkumaraswamydistributionwithitspropertiesandapplications
AT zafariqbal libbynovickkumaraswamydistributionwithitspropertiesandapplications
AT muhammadhanif libbynovickkumaraswamydistributionwithitspropertiesandapplications
AT munirahmad libbynovickkumaraswamydistributionwithitspropertiesandapplications
_version_ 1721193352867610624