Pedro Guilherme Costa Ferreira, Daiane Marcolino de Mattos
{"title":"用r来教季节调整","authors":"Pedro Guilherme Costa Ferreira, Daiane Marcolino de Mattos","doi":"10.12957/CADEST.2016.25077","DOIUrl":null,"url":null,"abstract":"DOI: 10.12957/cadest.2016.25077 This article shows, using R software, how to seasonally adjust a time series using the X-13-ARIMA-SEATS program and the seasonal package developed by Christoph Sax. In addition to presenting step-by-step seasonal adjustment, the article also explores how to analyze the program output and how to forecast the original and seasonally adjusted time series. A case study was proposed using the Brazilian industrial production. It was verified that the effect of Carnival, Easter and working days improved the seasonal adjustment when treated by the model. Keywords: Seasonal Adjustment, X13-ARIMA-SEATS, R software, RStudio.","PeriodicalId":30267,"journal":{"name":"Cadernos do IME Serie Estatistica","volume":"40 1","pages":"19"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.12957/CADEST.2016.25077","citationCount":"0","resultStr":"{\"title\":\"USING R TO TEACH SEASONAL ADJUSTMENT\",\"authors\":\"Pedro Guilherme Costa Ferreira, Daiane Marcolino de Mattos\",\"doi\":\"10.12957/CADEST.2016.25077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"DOI: 10.12957/cadest.2016.25077 This article shows, using R software, how to seasonally adjust a time series using the X-13-ARIMA-SEATS program and the seasonal package developed by Christoph Sax. In addition to presenting step-by-step seasonal adjustment, the article also explores how to analyze the program output and how to forecast the original and seasonally adjusted time series. A case study was proposed using the Brazilian industrial production. It was verified that the effect of Carnival, Easter and working days improved the seasonal adjustment when treated by the model. Keywords: Seasonal Adjustment, X13-ARIMA-SEATS, R software, RStudio.\",\"PeriodicalId\":30267,\"journal\":{\"name\":\"Cadernos do IME Serie Estatistica\",\"volume\":\"40 1\",\"pages\":\"19\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.12957/CADEST.2016.25077\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cadernos do IME Serie Estatistica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12957/CADEST.2016.25077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cadernos do IME Serie Estatistica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12957/CADEST.2016.25077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DOI: 10.12957/cadest.2016.25077 This article shows, using R software, how to seasonally adjust a time series using the X-13-ARIMA-SEATS program and the seasonal package developed by Christoph Sax. In addition to presenting step-by-step seasonal adjustment, the article also explores how to analyze the program output and how to forecast the original and seasonally adjusted time series. A case study was proposed using the Brazilian industrial production. It was verified that the effect of Carnival, Easter and working days improved the seasonal adjustment when treated by the model. Keywords: Seasonal Adjustment, X13-ARIMA-SEATS, R software, RStudio.