Double Lomax Distribution and its Applications

Punathumparambath Bindu () and Kulathinal Sangita ()
Additional contact information
Punathumparambath Bindu: Govt. Arts & Science College, Kozhikode, Kerala, India
Kulathinal Sangita: University of Helsinki, Finland

Statistica, 2015, vol. 75, issue 3, 331-342

Abstract: The Laplace distribution and its generalizations found applications in a variety of disciplines that range from image and speech recognition (input distributions) and ocean engineering to finance. In the present paper, our major goal is to study the family of distribution called the double Lomax distribution which is the ratio of two independent and identically distributed classical Laplace distributions. Also the double Lomax distribution can be obtained by compounding classical Laplace distribution with exponential density. The important statistical properties of double Lomax distribution are explored. Also the relationships with other families of distributions are established. Maximum likelihood estimation procedure is employed to estimate the parameters of the proposed distribution and an algorithm in R package is developed to carry out the estimation. A simulation study is conducted to validate the algorithm. Finally, the application of our model is illustrated. We have used a microarray data set for illustration.

Keywords: Double Lomax; Laplace; Microarray (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (3)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bot:rivsta:v:75:y:2015:i:3:p:331-342

Access Statistics for this article

Statistica is currently edited by Department of Statistics, University of Bologna

More articles in Statistica from Department of Statistics, University of Bologna Contact information at EDIRC.
Bibliographic data for series maintained by Giovanna Galatà ().