Alhaji Modu Isa, Sule Omeiza Bashiru, Alhaji Buhari Ali, Akeem Ajibola Adepoju, Ibrahim Ismaila Itopa
{"title":"正弦指数分布:数学性质及其在实际数据集上的应用","authors":"Alhaji Modu Isa, Sule Omeiza Bashiru, Alhaji Buhari Ali, Akeem Ajibola Adepoju, Ibrahim Ismaila Itopa","doi":"10.56919/usci.1122.017","DOIUrl":null,"url":null,"abstract":"To increase flexibility or to develop covariate models in various ways, new parameters can be added to existing families of distributions or a new family of distributions can be compounded with well-known standard normal distribution. In this paper, a trigonometric-type distribution was developed in order to come up with flexible distribution without adding parameters, considering Exponential distribution as the baseline distribution and Sine-G as the generator. The proposed distribution is referred to as Sine Exponential Distribution. Statistical features, including the moment, moment generating function, entropy, and order statistics were obtained. The proposed distribution's parameters were estimated using the Maximum Likelihood method. Using real datasets, the model's importance was demonstrated. The newly developed model was proven to be better than its competitors.","PeriodicalId":235595,"journal":{"name":"UMYU Scientifica","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Sine-Exponential Distribution: Its Mathematical Properties and Application to Real Dataset\",\"authors\":\"Alhaji Modu Isa, Sule Omeiza Bashiru, Alhaji Buhari Ali, Akeem Ajibola Adepoju, Ibrahim Ismaila Itopa\",\"doi\":\"10.56919/usci.1122.017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To increase flexibility or to develop covariate models in various ways, new parameters can be added to existing families of distributions or a new family of distributions can be compounded with well-known standard normal distribution. In this paper, a trigonometric-type distribution was developed in order to come up with flexible distribution without adding parameters, considering Exponential distribution as the baseline distribution and Sine-G as the generator. The proposed distribution is referred to as Sine Exponential Distribution. Statistical features, including the moment, moment generating function, entropy, and order statistics were obtained. The proposed distribution's parameters were estimated using the Maximum Likelihood method. Using real datasets, the model's importance was demonstrated. The newly developed model was proven to be better than its competitors.\",\"PeriodicalId\":235595,\"journal\":{\"name\":\"UMYU Scientifica\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"UMYU Scientifica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56919/usci.1122.017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"UMYU Scientifica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56919/usci.1122.017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sine-Exponential Distribution: Its Mathematical Properties and Application to Real Dataset
To increase flexibility or to develop covariate models in various ways, new parameters can be added to existing families of distributions or a new family of distributions can be compounded with well-known standard normal distribution. In this paper, a trigonometric-type distribution was developed in order to come up with flexible distribution without adding parameters, considering Exponential distribution as the baseline distribution and Sine-G as the generator. The proposed distribution is referred to as Sine Exponential Distribution. Statistical features, including the moment, moment generating function, entropy, and order statistics were obtained. The proposed distribution's parameters were estimated using the Maximum Likelihood method. Using real datasets, the model's importance was demonstrated. The newly developed model was proven to be better than its competitors.