Results 21 to 30 of about 165 (146)

Bayesian Estimation using Lindley’s Approximation and Prediction of Generalized Exponential Distribution Based on Lower Record Values

open access: yes, 2021
The two parameter generalized exponential distribution (which is denoted by GE(α,λ)) was introduced by Gupta and Kundu (1999). In this article, maximum likelihood estimators (MLE’s) for the two unknown parameters of the generalized exponential (GE ...
Faizan, Mohammad, Sana, Sana
core   +1 more source

Estimation of Reliability in Multi-Component Stress-Strength Model Following Exponentiated Pareto Distribution [PDF]

open access: yesThe Egyptian Statistical Journal, 2012
This article deals with the Bayesian and non-Bayesian estimation of reliability of an s-out-of-k system with identical component strengths which are subjected to a common stress. Assuming that both stress and strength are assumed to have an exponentiated
Heba M.Basheikh, Amal S.Hassan
doaj   +1 more source

Statistical Inference and Optimal Design of Accelerated Life Testing for the Chen Distribution under Progressive Type-II Censoring

open access: yesMathematics, 2022
This paper discusses statistical inference and optimal design of constant-stress accelerated life testing for the Chen distribution under progressive Type-II censoring.
Wenjie Zhang, Wenhao Gui
doaj   +1 more source

Bayes Estimator of Generalized-Exponential Parameters under Linex Loss Function Using Lindley's Approximation

open access: yesData Science Journal, 2008
In this paper, we have obtained the Bayes Estimator of Generalized-Exponential scale and shape parameter using Lindley's approximation (L-approximation) under asymmetric loss functions.
Rahul Singh   +3 more
doaj   +1 more source

Bayesian and Non-Bayesian Estimators of the Parameters of Weibull Distribution

open access: yes, 2021
In this paper, some estimators for the shape and scale parameters of Weibull distributionhave been obtained using Maximum likelihood as non-Bayesian estimators, as well asBayes estimators.
Abtisam J. Kadhim; Huda A. Rasheed
core   +1 more source

Reliability estimation and parameter estimation for inverse Weibull distribution under different loss functions

open access: yesKuwait Journal of Science, 2021
In this paper, the classical and Bayesian estimators of the unknown parameters and reliability function of the inverse Weibull distribution are considered.
Asuman Yılmaz, Mahmut Kara
doaj   +1 more source

Bayesian inference on reliability parameter with non-identical-component strengths for Rayleigh distribution [PDF]

open access: yesJournal of Mahani Mathematical Research
In this paper, we delve into Bayesian inference related to multi-component stress-strength parameters, focusing on non-identical component strengths within a two-parameter Rayleigh distribution under the progressive first failure censoring scheme.
Akram Kohansal
doaj   +1 more source

INFERENCES DRAWN ON COMMON SCALE PARAMETER OF TWO POPULATIONS USING RAINFALL DATA [PDF]

open access: yesProceedings on Engineering Sciences
This study investigates into the estimation of a common parameter across distinct probability distributions, including Weibull, Rayleigh, Gamma, and Lomax.
Vijay Kumar Lingutla   +2 more
doaj   +1 more source

Bayesian Estimation Using Product of Spacing for Modified Kies Exponential Progressively Censored Data

open access: yesAxioms, 2023
In life testing and reliability studies, most researchers have used the maximum likelihood estimation method to estimate unknown parameters, even though it has been proven that the maximum product of spacing method has properties as good as the maximum ...
Talal Kurdi   +2 more
doaj   +1 more source

Classical and Bayesian estimation of multicomponent stress–strength reliability for exponentiated Pareto distribution

open access: yes, 2021
This study deals with the classical and Bayesian estimation of reliability in a multicomponent stress–strength model by assuming that both stress and strength variables follow exponentiated Pareto distribution.
Akgül, Fatma Gül
core   +1 more source

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