Location Based Generalized Akash Distribution: Properties and Applications - Open Journal of Statistics

OJS > Vol.10 No.2, April 2020

Open Journal of Statistics

Volume 10, Issue 2 (April 2020)

ISSN Print: 2161-718X ISSN Online: 2161-7198

Google-based Impact Factor: 0.53 Citations

Location Based Generalized Akash Distribution: Properties and Applications ()

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Download as PDF (Size: 1107KB) PP. 163-187

DOI: 10.4236/ojs.2020.102013 592 Downloads 1,701 Views Citations

Author(s)

Ramajeyam Tharshan^1,2, Pushpakanthie Wijekoon³

Affiliation(s)

¹Postgraduate Institute of Science, University of Peradeniya, Peradeniya, Sri Lanka.
²Department of Mathematics and Statistics, University of Jaffna, Jaffna, Sri Lanka.
³Department of Statistics and Computer Science, University of Peradeniya, Peradeniya, Sri Lanka.

ABSTRACT

In recent years, several statistical finite mixture models have been proposed to model the lifetime data with heterogeneity. The Lindley distribution has been highlighted by many authors for these types of lifetime data analysis. This paper introduces a new Lindley family distribution called location-based generalized Akash distribution (NGAD) with monotonic increasing and bathtub failure rates. The density function of NGAD is flexible to cover the left-skewed, right-skewed and symmetrical shapes with different tail-weights. Its fundamental structural properties and its ability to provide a suitable statistical model for various types of data sets are studied. The maximum likelihood (ML) method is used to estimate its unknown parameters and the performance of ML estimates are examined by a simulation study. Finally, several real-data sets with different characteristics are used to illustrate its flexibility. It is observed that NGAD provides a better fit than some other existing modified Lindley distributions.

KEYWORDS

Lindley Distribution, Akash Distribution, Mixture

Share and Cite:

Tharshan, R. and Wijekoon, P. (2020) Location Based Generalized Akash Distribution: Properties and Applications. Open Journal of Statistics, 10, 163-187. doi: 10.4236/ojs.2020.102013.

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