Shumaila Ihtisham, Sadaf Manzoor, A. Khalil, S. Badshah, Muhammad Ijaz, H. Atta
{"title":"Modeling Extreme Values with Alpha Power Inverse Pareto Distribution","authors":"Shumaila Ihtisham, Sadaf Manzoor, A. Khalil, S. Badshah, Muhammad Ijaz, H. Atta","doi":"10.2478/msr-2023-0007","DOIUrl":null,"url":null,"abstract":"Abstract The study focuses on the development of a new probability distribution with applications to extreme values. The distribution is proposed by incorporating an additional parameter into the inverse Pareto distribution using the α-Power Transformation. Various properties of the new distribution are derived. The paper also explores the estimation of the parameters by the Maximum Likelihood Estimation (MLE) technique. Simulations are performed to evaluate the performance of the MLEs. In addition, two real data sets with extreme values are used to evaluate the efficacy of the proposed model. It is concluded that the proposed model performs well in the case of extreme values compared to the existing distributions.","PeriodicalId":49848,"journal":{"name":"Measurement Science Review","volume":"23 1","pages":"55 - 62"},"PeriodicalIF":1.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement Science Review","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.2478/msr-2023-0007","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The study focuses on the development of a new probability distribution with applications to extreme values. The distribution is proposed by incorporating an additional parameter into the inverse Pareto distribution using the α-Power Transformation. Various properties of the new distribution are derived. The paper also explores the estimation of the parameters by the Maximum Likelihood Estimation (MLE) technique. Simulations are performed to evaluate the performance of the MLEs. In addition, two real data sets with extreme values are used to evaluate the efficacy of the proposed model. It is concluded that the proposed model performs well in the case of extreme values compared to the existing distributions.
期刊介绍：
- theory of measurement - mathematical processing of measured data - measurement uncertainty minimisation - statistical methods in data evaluation and modelling - measurement as an interdisciplinary activity - measurement science in education - medical imaging methods, image processing - biosignal measurement, processing and analysis - model based biomeasurements - neural networks in biomeasurement - telemeasurement in biomedicine - measurement in nanomedicine - measurement of basic physical quantities - magnetic and electric fields measurements - measurement of geometrical and mechanical quantities - optical measuring methods - electromagnetic compatibility - measurement in material science
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