{"title":"对数正态和的简单α-μ近似","authors":"Bing Wang, G. Cui, L. Kong, Wei Yi","doi":"10.1109/RADAR.2014.6875632","DOIUrl":null,"url":null,"abstract":"In this paper, we adopt the α-μ distribution to approximate the statistic distribution of the sum of independent and possibly non-identically distributed lognormal variables, and obtain the shape and scale parameters using both the moment matching method and Non-linear Least Square Method. Finally, we evaluate the performance via numerical simulations, the results illustrate that the α-μ approximation fits well the sum of the lognormal variables.","PeriodicalId":127690,"journal":{"name":"2014 IEEE Radar Conference","volume":"192 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Simple α-μ approximation to lognormal sums\",\"authors\":\"Bing Wang, G. Cui, L. Kong, Wei Yi\",\"doi\":\"10.1109/RADAR.2014.6875632\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we adopt the α-μ distribution to approximate the statistic distribution of the sum of independent and possibly non-identically distributed lognormal variables, and obtain the shape and scale parameters using both the moment matching method and Non-linear Least Square Method. Finally, we evaluate the performance via numerical simulations, the results illustrate that the α-μ approximation fits well the sum of the lognormal variables.\",\"PeriodicalId\":127690,\"journal\":{\"name\":\"2014 IEEE Radar Conference\",\"volume\":\"192 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Radar Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADAR.2014.6875632\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Radar Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADAR.2014.6875632","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we adopt the α-μ distribution to approximate the statistic distribution of the sum of independent and possibly non-identically distributed lognormal variables, and obtain the shape and scale parameters using both the moment matching method and Non-linear Least Square Method. Finally, we evaluate the performance via numerical simulations, the results illustrate that the α-μ approximation fits well the sum of the lognormal variables.
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