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The Power XLindley Distribution: Statistical Inference, Fuzzy Reliability, and COVID-19 Application

Meriem Bouhadjar, Ahmed M. Gemeay, Ehab M. Almetwally, Halim Zeghdoudi, Etaf Alshawarbeh, Alanazi Talal Abdulrahman, M. M. Abd El‐Raouf, Eslam Hussam

2022Journal of Function Spaces42 citationsDOIOpen Access PDF

Abstract

The power XLindley (PXL) distribution is introduced in this study. It is a two-parameter distribution that extends the XLindley distribution established in this paper. Numerous statistical characteristics of the suggested model were determined analytically. The proposed model’s fuzzy dependability was statistically assessed. Numerous estimation techniques have been devised for the purpose of estimating the proposed model parameters. The behaviour of these factors was examined using randomly generated data and developed estimation approaches. The suggested model seems to be superior to its base model and other well-known and related models when applied to the COVID-19 data set.

Topics & Concepts

Reliability (semiconductor)Computer scienceDependabilityStatistical inferenceFuzzy logicData miningData setEstimationCoronavirus disease 2019 (COVID-19)Statistical modelSet (abstract data type)Power (physics)StatisticsReliability engineeringMathematicsArtificial intelligenceEngineeringDiseasePhysicsMedicineQuantum mechanicsSystems engineeringInfectious disease (medical specialty)PathologyProgramming languageStatistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering DesignAdvanced Statistical Methods and Models
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