{"title":"论使用阿尔法幂变换余弦矩指数模型分析环境和工程数据","authors":"Hleil Alrweili","doi":"10.28924/2291-8639-22-2024-99","DOIUrl":null,"url":null,"abstract":"This article introduces a new model using the alpha power cosine transformed method for modeling complex data used in hydrology and engineering studies. The alpha power novel distribution transformed the cosine moment exponential model with two parameters. Its probability density function can be skewed and unimodal. Various statistical and mathematical properties are established, and the unknown parameters of the suggested model are determined using numerous estimation procedures. Also, the potential of these estimation techniques is calculated via some simulation studies. In the end, two real data sets are made using the proposed model to make a practical application in environmental and survival fields. The potential and utility of the recommended distribution are verified with other well known models and it shows great superiority in fitting the proposed data sets.","PeriodicalId":45204,"journal":{"name":"International Journal of Analysis and Applications","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model\",\"authors\":\"Hleil Alrweili\",\"doi\":\"10.28924/2291-8639-22-2024-99\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article introduces a new model using the alpha power cosine transformed method for modeling complex data used in hydrology and engineering studies. The alpha power novel distribution transformed the cosine moment exponential model with two parameters. Its probability density function can be skewed and unimodal. Various statistical and mathematical properties are established, and the unknown parameters of the suggested model are determined using numerous estimation procedures. Also, the potential of these estimation techniques is calculated via some simulation studies. In the end, two real data sets are made using the proposed model to make a practical application in environmental and survival fields. The potential and utility of the recommended distribution are verified with other well known models and it shows great superiority in fitting the proposed data sets.\",\"PeriodicalId\":45204,\"journal\":{\"name\":\"International Journal of Analysis and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2024-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Analysis and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.28924/2291-8639-22-2024-99\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Analysis and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28924/2291-8639-22-2024-99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model
This article introduces a new model using the alpha power cosine transformed method for modeling complex data used in hydrology and engineering studies. The alpha power novel distribution transformed the cosine moment exponential model with two parameters. Its probability density function can be skewed and unimodal. Various statistical and mathematical properties are established, and the unknown parameters of the suggested model are determined using numerous estimation procedures. Also, the potential of these estimation techniques is calculated via some simulation studies. In the end, two real data sets are made using the proposed model to make a practical application in environmental and survival fields. The potential and utility of the recommended distribution are verified with other well known models and it shows great superiority in fitting the proposed data sets.