Silvia Herrera Cortés, Bulmaro Juárez Hernández, Víctor Hugo Vázquez Guevara, H. A. Cruz Suárez
{"title":"Parametric Methodologies for Detecting Changes in Maximum Temperature of Tlaxco, Tlaxcala, México","authors":"Silvia Herrera Cortés, Bulmaro Juárez Hernández, Víctor Hugo Vázquez Guevara, H. A. Cruz Suárez","doi":"10.1155/2019/3580692","DOIUrl":null,"url":null,"abstract":"In this paper, comparison results of parametric methodologies of change points, applied to maximum temperature records from the municipality of Tlaxco, Tlaxcala, Mexico, are presented. Methodologies considered are likelihood ratio test, score test, and binary segmentation (BS), pruned exact linear time (PELT), and segment neighborhood (SN). In order to compare such methodologies, a quality analysis of the data was performed; in addition, lost data were estimated with linear regression, and finally, SARIMA models were adjusted.","PeriodicalId":44760,"journal":{"name":"Journal of Probability and Statistics","volume":"2019 1","pages":"1-14"},"PeriodicalIF":1.0000,"publicationDate":"2019-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/3580692","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Probability and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2019/3580692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
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Abstract
In this paper, comparison results of parametric methodologies of change points, applied to maximum temperature records from the municipality of Tlaxco, Tlaxcala, Mexico, are presented. Methodologies considered are likelihood ratio test, score test, and binary segmentation (BS), pruned exact linear time (PELT), and segment neighborhood (SN). In order to compare such methodologies, a quality analysis of the data was performed; in addition, lost data were estimated with linear regression, and finally, SARIMA models were adjusted.
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