Efficient Estimation of the Generalized Quasi-Lindley Distribution Parameters under Ranked Set Sampling and Applications

Al-Omari, Amer Ibrahim; Benchiha, SidAhmed; Almanjahie, Ibrahim M.

doi:10.1155/2021/9982397

Cited by 13 publications

(2 citation statements)

References 40 publications

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“…where Ss = sample size, Z = z-value representing the data's confidence level, P(1 − p) = response variance, and Me = margin of error or sampling error. The margin of error for this survey study was 10%, the Z-score was 1.96 (for a two-tailed alternate hypothesis at α = 0.05), and the sample proportion was 50% for simple random sampling [87,88]. Therefore, the minimum sample size required to examine the risk factors associated with the use of ImTs was 97 respondents.…”

Section: Survey Distributionmentioning

confidence: 99%

Immersive Technology Implementation in the Construction Industry: Modeling Paths of Risk

2022

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The purposes of this paper are to identify risk factors impacting the successful implementation of immersive reality technology (ImT) in the construction industry, analyze these risk factors (impact and probability), assess the relationships among different categories of risk factors, and provide recommendations to improve ImT implementation. A literature review, a pilot test based on expert interviews, and a questionnaire survey were used. First, the risk factors of ImT applications were identified by consulting the relevant literature on virtual reality, mixed reality, and augmented reality; these were subsequently grouped into five categories—technology, operation, individual/worker, investment, and external. Next, a questionnaire survey was designed and distributed to relevant construction practitioners in South Africa (usable response = 175). Twenty-one ImT implementation risk factors were identified, and risk criticality scores ranged from 2.02 to 3.18. High investment cost, the need for extensive worker training, and the possible introduction of new risks for workers were rated as significant risks. The present study confirmed three statistically significant hypothesized risk paths—namely, those between external issues and individual/worker’s concerns, between external issues and investment limitations, and between individual/worker’s concerns and technology concerns. The present study contributes to the literature regarding the adoption of construction technology by providing a list of critical risk factors that could be used to develop models and tools for assessing ImT adoption and guide practitioners involved in integrating ImTs.

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Section: Survey Distributionmentioning

confidence: 99%

Immersive Technology Implementation in the Construction Industry: Modeling Paths of Risk

2022

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“…[53] for the Birnbaum-Saunders distribution, Ref. [54] for the generalized quasi-Lindley distribution, Ref. [55] for the Weibull distribution, and Ref.…”

Section: Introductionmentioning

confidence: 99%

Bayesian and Non-Bayesian Estimation for a New Extension of Power Topp–Leone Distribution under Ranked Set Sampling with Applications

Alotaibi

Al-Moisheer

Elbatal

et al. 2023

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In this article, we intend to introduce and study a new two-parameter distribution as a new extension of the power Topp–Leone (PTL) distribution called the Kavya–Manoharan PTL (KMPTL) distribution. Several mathematical and statistical features of the KMPTL distribution, such as the quantile function, moments, generating function, and incomplete moments, are calculated. Some measures of entropy are investigated. The cumulative residual Rényi entropy (CRRE) is calculated. To estimate the parameters of the KMPTL distribution, both maximum likelihood and Bayesian estimation methods are used under simple random sample (SRS) and ranked set sampling (RSS). The simulation study was performed to be able to verify the model parameters of the KMPTL distribution using SRS and RSS to demonstrate that RSS is more efficient than SRS. We demonstrated that the KMPTL distribution has more flexibility than the PTL distribution and the other nine competitive statistical distributions: PTL, unit-Gompertz, unit-Lindley, Topp–Leone, unit generalized log Burr XII, unit exponential Pareto, Kumaraswamy, beta, Marshall-Olkin Kumaraswamy distributions employing two real-world datasets.

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A new modified model with application to engineering data sets

Alsadat¹

2023

Alexandria Engineering Journal

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Efficient Estimation of the Generalized Quasi-Lindley Distribution Parameters under Ranked Set Sampling and Applications

Cited by 13 publications

References 40 publications

Immersive Technology Implementation in the Construction Industry: Modeling Paths of Risk

Immersive Technology Implementation in the Construction Industry: Modeling Paths of Risk

Bayesian and Non-Bayesian Estimation for a New Extension of Power Topp–Leone Distribution under Ranked Set Sampling with Applications

A new modified model with application to engineering data sets

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