{"title":"时间序列非线性创新模型。","authors":"D. Ebong","doi":"10.4314/GJMAS.V9I1.62500","DOIUrl":null,"url":null,"abstract":"This paper introduces a class of nonlinear innovation process that has similar properties as the white noise process. Consequently the process can be a replacement of the white noise process in cases where the latter is inadequate as residual process. KEYWORDS: Asymptotic distribution of autocorrelation, nonlinear errors, nonlinear residuals, nonlinear time series","PeriodicalId":126381,"journal":{"name":"Global Journal of Mathematical Sciences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A model for nonlinear innovation in time series.\",\"authors\":\"D. Ebong\",\"doi\":\"10.4314/GJMAS.V9I1.62500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a class of nonlinear innovation process that has similar properties as the white noise process. Consequently the process can be a replacement of the white noise process in cases where the latter is inadequate as residual process. KEYWORDS: Asymptotic distribution of autocorrelation, nonlinear errors, nonlinear residuals, nonlinear time series\",\"PeriodicalId\":126381,\"journal\":{\"name\":\"Global Journal of Mathematical Sciences\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Journal of Mathematical Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/GJMAS.V9I1.62500\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Journal of Mathematical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/GJMAS.V9I1.62500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper introduces a class of nonlinear innovation process that has similar properties as the white noise process. Consequently the process can be a replacement of the white noise process in cases where the latter is inadequate as residual process. KEYWORDS: Asymptotic distribution of autocorrelation, nonlinear errors, nonlinear residuals, nonlinear time series
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