期刊论文详细信息
Entropy 卷:23
The Truncated Burr X-G Family of Distributions: Properties and Applications to Actuarial and Financial Data
Rashad A. R. Bantan1  Ibrahim Elbatal2  Christophe Chesneau3  Farrukh Jamal4  Mohammed Elgarhy5 
[1] Department of Marine Geology, Faculty of Marine Science, King AbdulAziz University, Jeddah 21551, Saudi Arabia;
[2] Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia;
[3] Department of Mathematics, Université de Caen, LMNO, Campus II, Science 3, 14032 Caen, France;
[4] Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan;
[5] The Higher Institute of Commercial Sciences, Al mahalla Al kubra, Algarbia 31951, Egypt;
关键词: truncated distributions;    Burr X distribution;    general family of distributions;    moments;    risk measures;    maximum likelihood technique;   
DOI  :  10.3390/e23081088
来源: DOAJ
【 摘 要 】

In this article, the “truncated-composed” scheme was applied to the Burr X distribution to motivate a new family of univariate continuous-type distributions, called the truncated Burr X generated family. It is mathematically simple and provides more modeling freedom for any parental distribution. Additional functionality is conferred on the probability density and hazard rate functions, improving their peak, asymmetry, tail, and flatness levels. These characteristics are represented analytically and graphically with three special distributions of the family derived from the exponential, Rayleigh, and Lindley distributions. Subsequently, we conducted asymptotic, first-order stochastic dominance, series expansion, Tsallis entropy, and moment studies. Useful risk measures were also investigated. The remainder of the study was devoted to the statistical use of the associated models. In particular, we developed an adapted maximum likelihood methodology aiming to efficiently estimate the model parameters. The special distribution extending the exponential distribution was applied as a statistical model to fit two sets of actuarial and financial data. It performed better than a wide variety of selected competing non-nested models. Numerical applications for risk measures are also given.

【 授权许可】

Unknown   

  文献评价指标  
  下载次数:0次 浏览次数:0次