z-logo
open-access-imgOpen Access
New Lindley Half Cauchy Distribution Theory and Applications
Author(s) -
Arun Kumar Chaudhary,
Vijay Kumar
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d4734.119420
Subject(s) - cauchy distribution , kurtosis , mathematics , quantile , estimator , likelihood function , statistics , quantile function , asymptotic distribution , cumulative distribution function , probability density function , estimation theory
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here