{"title":"相关噪声情况下线性回归置信带的估计","authors":"A. Chunovkina, A. Stepanov","doi":"10.23919/MEASUREMENT47340.2019.8779916","DOIUrl":null,"url":null,"abstract":"Basing on generalized least squares method and Monte Carlo simulation techniques, linear regression confidence bands are calculated in the case of correlated noise. Exponentially correlated Gaussian noise is considered. Comparison with the confidence band obtained for white noise is presented using the methodology of metrological assessment of measurement data processing algorithms.","PeriodicalId":129350,"journal":{"name":"2019 12th International Conference on Measurement","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Estimation of Linear Regression Confidence Bands in Case of Correlated Noise\",\"authors\":\"A. Chunovkina, A. Stepanov\",\"doi\":\"10.23919/MEASUREMENT47340.2019.8779916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Basing on generalized least squares method and Monte Carlo simulation techniques, linear regression confidence bands are calculated in the case of correlated noise. Exponentially correlated Gaussian noise is considered. Comparison with the confidence band obtained for white noise is presented using the methodology of metrological assessment of measurement data processing algorithms.\",\"PeriodicalId\":129350,\"journal\":{\"name\":\"2019 12th International Conference on Measurement\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 12th International Conference on Measurement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/MEASUREMENT47340.2019.8779916\",\"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 12th International Conference on Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MEASUREMENT47340.2019.8779916","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of Linear Regression Confidence Bands in Case of Correlated Noise
Basing on generalized least squares method and Monte Carlo simulation techniques, linear regression confidence bands are calculated in the case of correlated noise. Exponentially correlated Gaussian noise is considered. Comparison with the confidence band obtained for white noise is presented using the methodology of metrological assessment of measurement data processing algorithms.
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