Journal ArticleDOI
Inferences on Stress-Strength Reliability from Weighted Lindley Distributions
TLDR
In this paper, the estimation of the stress-strength parameter R = P(Y < X), when X and Y are two independent weighted Lindley random variables with a common shape parameter, is dealt with.Abstract:
This article deals with the estimation of the stress-strength parameter R = P(Y < X), when X and Y are two independent weighted Lindley random variables with a common shape parameter. The MLEs can be obtained by maximizing the profile log-likelihood function in one dimension. The asymptotic distribution of the MLEs are also obtained, and they have been used to construct the asymptotic confidence interval of R. Bootstrap confidence intervals are also proposed. Monte Carlo simulations are performed to verify the effectiveness of the different estimation methods, and data analysis has been performed for illustrative purposes.read more
Citations
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Journal ArticleDOI
Reliability estimation of a N-M-cold-standby redundancy system in a multicomponent stress–strength model with generalized half-logistic distribution
TL;DR: In this article, the estimation for the reliability of a multicomponent system, named N - M -cold-standby redundancy system, based on progressive Type-II censoring sample, is studied.
Journal ArticleDOI
Bayesian analysis of head and neck cancer data using generalized inverse Lindley stress–strength reliability model
TL;DR: In this paper, the authors presented the analysis of head and neck cancer data using generalized inverse Lindley stress-strength reliability model and proposed Bayes estimators for estimating P(X > Y), when X and Y represent survival times of two groups of cancer patients observed under different therapies.
Journal ArticleDOI
The generalized weighted Lindley distribution: Properties, estimation, and applications
TL;DR: In this paper, a three-parameter lifetime distribution named generalized weighted Lindley (GLW) distribution is proposed, which is a useful generalization of the weighted lindley distribution.
Journal ArticleDOI
Higher order moments of order statistics from the Lindley distribution and associated inference
TL;DR: The authors derived explicit expressions for the single, double (product), triple and quadruple moments of order statistics from the Lindley distribution and used these moments to obtain the best linear unbiased estimates (BLUEs) of the location and scale parameters based on Type-II right-censored samples.
Journal ArticleDOI
The Marshall–Olkin extended generalized Lindley distribution: Properties and applications
TL;DR: A new three-parameter model called the Marshall–Olkin extended generalized Lindley distribution is defined and study, including expansions for the density function, ordinary moments, moment generating function, quantile function, mean deviations, Bonferroni and Lorenz curves, order statistics and their moments, Rényi entropy and reliability.
References
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Journal ArticleDOI
Generalized Exponential Distributions
Rameshwar D. Gupta,Debasis Kundu +1 more
TL;DR: In this article, a three-parameter generalized exponential distribution (GED) was used for analysis of lifetime data, which is a particular case of the exponentiated Weibull distribution originally proposed by Mudholkar et al.
Book
Special Functions of Mathematics for Engineers
TL;DR: This book systematically introduces important special functions and explores their salient properties and is suitable as a classroom textbook in courses dealing with higher mathematical functions or as a reference text for practicing engineers and scientists.
Journal ArticleDOI
Lindley distribution and its application
TL;DR: A treatment of the mathematical properties is provided for the Lindley distribution, which includes moments, cumulants, characteristic function, failure rate function, mean residual life function, and mean deviations.