TY - JOUR
T1 - A new class of Lindley distribution
T2 - System reliability, simulation and applications
AU - Qayoom, Danish
AU - Rather, Aafaq A.
AU - Alsadat, Najwan
AU - Hussam, Eslam
AU - Gemeay, Ahmed M.
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/10/15
Y1 - 2024/10/15
N2 - This paper presents a new probability distribution called the DUS Lindley distribution, created by applying the DUS transformation to the traditional Lindley distribution. The study provides an in-depth analysis of the distribution's statistical properties. These properties include a variety of statistical measures such as the probability density function, cumulative distribution function, failure rate, survival function, reverse hazard function, Mills ratio, mean residual life, mean past life, moments, conditional moments, characteristic function, order statistics, entropy measures, likelihood ratio test and Lorenz and Bonferroni curves. Parameter estimation is performed using several methods including weighted least squares, maximum likelihood estimation, Cramer-Von Mises estimation, least squares and Anderson-Darling estimation. The paper also explores the estimation of system reliability and evaluates the performance of maximum likelihood estimators through simulation studies across different sample sizes. Finally, the DUS Lindley distribution is applied to two real-world datasets, demonstrating a better fit than other well-known distributions.
AB - This paper presents a new probability distribution called the DUS Lindley distribution, created by applying the DUS transformation to the traditional Lindley distribution. The study provides an in-depth analysis of the distribution's statistical properties. These properties include a variety of statistical measures such as the probability density function, cumulative distribution function, failure rate, survival function, reverse hazard function, Mills ratio, mean residual life, mean past life, moments, conditional moments, characteristic function, order statistics, entropy measures, likelihood ratio test and Lorenz and Bonferroni curves. Parameter estimation is performed using several methods including weighted least squares, maximum likelihood estimation, Cramer-Von Mises estimation, least squares and Anderson-Darling estimation. The paper also explores the estimation of system reliability and evaluates the performance of maximum likelihood estimators through simulation studies across different sample sizes. Finally, the DUS Lindley distribution is applied to two real-world datasets, demonstrating a better fit than other well-known distributions.
KW - Bonferroni and lorenz curves
KW - DUS transformation
KW - Entropy
KW - Lindley distribution
KW - Simulation
KW - System reliability
UR - http://www.scopus.com/inward/record.url?scp=85205232760&partnerID=8YFLogxK
U2 - 10.1016/j.heliyon.2024.e38335
DO - 10.1016/j.heliyon.2024.e38335
M3 - Article
AN - SCOPUS:85205232760
SN - 2405-8440
VL - 10
JO - Heliyon
JF - Heliyon
IS - 19
M1 - e38335
ER -