{"title":"一些新的脊回归估计的性能","authors":"M. Suhail, S. Chand","doi":"10.1109/MACS48846.2019.9024784","DOIUrl":null,"url":null,"abstract":"Ridge regression is used to circumvent the effect of multicollinearity. Ridge parameter plays an important role in reducing the variance of ridge estimators. In this paper, we consider some existing estimators and propose some new ridge regression estimators for linear regression models. The performance of estimators is evaluated through a Monte Carlo simulation study. Based on mean square error criterion, our proposed estimators show some better performance as compared to other considered ridge estimators. An application is also given to illustrate the simulation results.","PeriodicalId":434612,"journal":{"name":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Performance of some new ridge regression estimators\",\"authors\":\"M. Suhail, S. Chand\",\"doi\":\"10.1109/MACS48846.2019.9024784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ridge regression is used to circumvent the effect of multicollinearity. Ridge parameter plays an important role in reducing the variance of ridge estimators. In this paper, we consider some existing estimators and propose some new ridge regression estimators for linear regression models. The performance of estimators is evaluated through a Monte Carlo simulation study. Based on mean square error criterion, our proposed estimators show some better performance as compared to other considered ridge estimators. An application is also given to illustrate the simulation results.\",\"PeriodicalId\":434612,\"journal\":{\"name\":\"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MACS48846.2019.9024784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MACS48846.2019.9024784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance of some new ridge regression estimators
Ridge regression is used to circumvent the effect of multicollinearity. Ridge parameter plays an important role in reducing the variance of ridge estimators. In this paper, we consider some existing estimators and propose some new ridge regression estimators for linear regression models. The performance of estimators is evaluated through a Monte Carlo simulation study. Based on mean square error criterion, our proposed estimators show some better performance as compared to other considered ridge estimators. An application is also given to illustrate the simulation results.