10.35940/ijrte.D4734.119420
https://zenodo.org/records/5835182
oai:zenodo.org:5835182
Arun Kumar Chaudhary
Arun Kumar Chaudhary
Associate Professor, Department of Management Science, Nepal Commerce Campus, Tribhuwan University, Nepal,
Vijay Kumar
Vijay Kumar
Department of Mathematics and Statistics, DDU Gorakhpur University, Gorakhpur, India.
New Lindley Half Cauchy Distribution: Theory and Applications
Zenodo
2020
Estimation, Generalized Rayleigh (GR) distribution, Half-Cauchy distribution, Lindley distribution
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)
Publisher
2020-11-30
eng
2277-3878
Creative Commons Attribution 4.0 International
In this paper, we have defined a new two-parameter new Lindley half Cauchy (NLHC) distribution using Lindley-G family of distribution which accommodates increasing, decreasing and a variety of monotone failure rates. The statistical properties of the proposed distribution such as probability density function, cumulative distribution function, quantile, the measure of skewness and kurtosis are presented. We have briefly described the three well-known estimation methods namely maximum likelihood estimators (MLE), least-square (LSE) and Cramer-Von-Mises (CVM) methods. All the computations are performed in R software. By using the maximum likelihood method, we have constructed the asymptotic confidence interval for the model parameters. We verify empirically the potentiality of the new distribution in modeling a real data set.