{"title":"引入一种新的线性危害率函数参数估计","authors":"Lekaa Ali Mohamed","doi":"10.5251/AJSIR.2013.4.1.36.43","DOIUrl":null,"url":null,"abstract":"This paper deals with introducing four estimators of parameters ( ), for linear hazard (risk) function { }. Two consist of the proposed which are mixed estimators, and the proposed estimator depend on order record data. While the two other methods, include maximum likelihood method which are solved numerically, using Newton Raphson method, and last method is white estimators depend on principle of least square's method. The comparison between ( ), has been done through simulation experiment for different sample size chosen and replicate is ( ). The statistical measure mean square error (MSE) is used for comparison. All results are explained through tables, for different sets of chosen parameters. Keyword: Hazard rate { }, maximum likelihood, OLS, proposed method, mean square error (MSE).","PeriodicalId":7661,"journal":{"name":"American Journal of Scientific and Industrial Research","volume":"35 1","pages":"36-43"},"PeriodicalIF":0.0000,"publicationDate":"2013-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Introducing a New Estimators of Parameters of Linear Hazard Rate Function\",\"authors\":\"Lekaa Ali Mohamed\",\"doi\":\"10.5251/AJSIR.2013.4.1.36.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with introducing four estimators of parameters ( ), for linear hazard (risk) function { }. Two consist of the proposed which are mixed estimators, and the proposed estimator depend on order record data. While the two other methods, include maximum likelihood method which are solved numerically, using Newton Raphson method, and last method is white estimators depend on principle of least square's method. The comparison between ( ), has been done through simulation experiment for different sample size chosen and replicate is ( ). The statistical measure mean square error (MSE) is used for comparison. All results are explained through tables, for different sets of chosen parameters. Keyword: Hazard rate { }, maximum likelihood, OLS, proposed method, mean square error (MSE).\",\"PeriodicalId\":7661,\"journal\":{\"name\":\"American Journal of Scientific and Industrial Research\",\"volume\":\"35 1\",\"pages\":\"36-43\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Journal of Scientific and Industrial Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5251/AJSIR.2013.4.1.36.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Scientific and Industrial Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5251/AJSIR.2013.4.1.36.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Introducing a New Estimators of Parameters of Linear Hazard Rate Function
This paper deals with introducing four estimators of parameters ( ), for linear hazard (risk) function { }. Two consist of the proposed which are mixed estimators, and the proposed estimator depend on order record data. While the two other methods, include maximum likelihood method which are solved numerically, using Newton Raphson method, and last method is white estimators depend on principle of least square's method. The comparison between ( ), has been done through simulation experiment for different sample size chosen and replicate is ( ). The statistical measure mean square error (MSE) is used for comparison. All results are explained through tables, for different sets of chosen parameters. Keyword: Hazard rate { }, maximum likelihood, OLS, proposed method, mean square error (MSE).