{"title":"具有长期相关性的时间序列的拟合优度检验","authors":"J. Beran","doi":"10.1111/J.2517-6161.1992.TB01448.X","DOIUrl":null,"url":null,"abstract":"We propose a test statistic for goodness of fit in time series with slowly decaying serial correlations. The asymptotic distribution of the test statistic, originally proposed by Milhoj for time series with smooth spectra, turns out to be the same, under the null hypothesis, even if the spectrum has a pole at 0. In particular, the test is suitable to detect lack of independence in the observations, or estimated residuals, if the first few correlations are small but the decay of the correlations is slow","PeriodicalId":17425,"journal":{"name":"Journal of the royal statistical society series b-methodological","volume":"14 1","pages":"749-760"},"PeriodicalIF":0.0000,"publicationDate":"1992-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"89","resultStr":"{\"title\":\"A Goodness‐Of‐Fit Test for Time Series with Long Range Dependence\",\"authors\":\"J. Beran\",\"doi\":\"10.1111/J.2517-6161.1992.TB01448.X\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a test statistic for goodness of fit in time series with slowly decaying serial correlations. The asymptotic distribution of the test statistic, originally proposed by Milhoj for time series with smooth spectra, turns out to be the same, under the null hypothesis, even if the spectrum has a pole at 0. In particular, the test is suitable to detect lack of independence in the observations, or estimated residuals, if the first few correlations are small but the decay of the correlations is slow\",\"PeriodicalId\":17425,\"journal\":{\"name\":\"Journal of the royal statistical society series b-methodological\",\"volume\":\"14 1\",\"pages\":\"749-760\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"89\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the royal statistical society series b-methodological\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/J.2517-6161.1992.TB01448.X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the royal statistical society series b-methodological","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/J.2517-6161.1992.TB01448.X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Goodness‐Of‐Fit Test for Time Series with Long Range Dependence
We propose a test statistic for goodness of fit in time series with slowly decaying serial correlations. The asymptotic distribution of the test statistic, originally proposed by Milhoj for time series with smooth spectra, turns out to be the same, under the null hypothesis, even if the spectrum has a pole at 0. In particular, the test is suitable to detect lack of independence in the observations, or estimated residuals, if the first few correlations are small but the decay of the correlations is slow