{"title":"Families of distributions arising from the quantile of generalized lambda distribution","authors":"Mahmoud Aldeni, Carl Lee, Felix Famoye","doi":"10.1186/s40488-017-0081-4","DOIUrl":null,"url":null,"abstract":"In this paper, the class of T-R {generalized lambda} families of distributions based on the quantile of generalized lambda distribution has been proposed using the T-R{Y} framework. In the development of the T-R{Y} framework, the support of Y and T must be the same. It is typical that the random variable Y has one type of support and T is restricted to the same support. Taking Y to be a generalized lambda random variable leads to three different types of supports, thus, making the choice of the generator T to be much more broad and flexible. This is interesting and unique. By allowing T with different supports makes the T-R{generalized lambda} a desirable method for generating new versatile and broad families of generalized distributions for any given random variable R. Some general properties of these families of distributions are studied. Four members of the T-R{generalized lambda} families of distributions are derived. The shapes of these distributions can be symmetric, skewed to the left, skewed to the right, or bimodal. Two real life data sets are applied to illustrate the flexibility of the distributions.","PeriodicalId":52216,"journal":{"name":"Journal of Statistical Distributions and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Distributions and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s40488-017-0081-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 27
Abstract
In this paper, the class of T-R {generalized lambda} families of distributions based on the quantile of generalized lambda distribution has been proposed using the T-R{Y} framework. In the development of the T-R{Y} framework, the support of Y and T must be the same. It is typical that the random variable Y has one type of support and T is restricted to the same support. Taking Y to be a generalized lambda random variable leads to three different types of supports, thus, making the choice of the generator T to be much more broad and flexible. This is interesting and unique. By allowing T with different supports makes the T-R{generalized lambda} a desirable method for generating new versatile and broad families of generalized distributions for any given random variable R. Some general properties of these families of distributions are studied. Four members of the T-R{generalized lambda} families of distributions are derived. The shapes of these distributions can be symmetric, skewed to the left, skewed to the right, or bimodal. Two real life data sets are applied to illustrate the flexibility of the distributions.
本文利用T-R{Y}框架,基于广义λ分布的分位数,提出了一类T-R{广义λ}族分布。在开发T- r {Y}框架时,Y和T的支持必须是相同的。典型的情况是,随机变量Y有一种支持,而T被限制为同一种支持。将Y作为广义的lambda随机变量,可以得到三种不同类型的支撑,从而使发电机T的选择更加广泛和灵活。这很有趣,也很独特。通过允许T具有不同的支撑点,使得T- r{广义λ}成为对任意给定的随机变量r生成新的通用的广义分布族的理想方法。导出了T-R{广义λ}族分布的四个成员。这些分布的形状可以是对称的、向左倾斜的、向右倾斜的或双峰的。本文应用了两个实际数据集来说明分布的灵活性。