000118975 001__ 118975
000118975 005__ 20240319081013.0
000118975 0247_ $$2doi$$a10.1007/s10651-022-00539-2
000118975 0248_ $$2sideral$$a130160
000118975 037__ $$aART-2022-130160
000118975 041__ $$aeng
000118975 100__ $$0(orcid)0000-0003-3859-0248$$aCastillo Mateo, Jorge$$uUniversidad de Zaragoza
000118975 245__ $$aDistribution-free changepoint detection tests based on the breaking of records
000118975 260__ $$c2022
000118975 5060_ $$aAccess copy available to the general public$$fUnrestricted
000118975 5203_ $$aThe analysis of record-breaking events is of interest in fields such as climatology, hydrology or anthropology. In connection with the record occurrence, we propose three distribution-free statistics for the changepoint detection problem. They are CUSUM-type statistics based on the upper and/or lower record indicators observed in a series. Using a version of the functional central limit theorem, we show that the CUSUM-type statistics are asymptotically Kolmogorov distributed. The main results under the null hypothesis are based on series of independent and identically distributed random variables, but a statistic to deal with series with seasonal component and serial correlation is also proposed. A Monte Carlo study of size, power and changepoint estimate has been performed. Finally, the methods are illustrated by analyzing the time series of temperatures at Madrid, Spain. The R package RecordTest publicly available on CRAN implements the proposed methods.
000118975 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E46-20R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-116873GB-I00
000118975 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000118975 590__ $$a3.8$$b2022
000118975 592__ $$a0.556$$b2022
000118975 591__ $$aSTATISTICS & PROBABILITY$$b13 / 125 = 0.104$$c2022$$dQ1$$eT1
000118975 593__ $$aEnvironmental Science (miscellaneous)$$c2022$$dQ2
000118975 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b19 / 107 = 0.178$$c2022$$dQ1$$eT1
000118975 593__ $$aStatistics, Probability and Uncertainty$$c2022$$dQ2
000118975 591__ $$aENVIRONMENTAL SCIENCES$$b119 / 275 = 0.433$$c2022$$dQ2$$eT2
000118975 593__ $$aStatistics and Probability$$c2022$$dQ2
000118975 594__ $$a4.0$$b2022
000118975 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000118975 7102_ $$12007$$2265$$aUniversidad de Zaragoza$$bDpto. Métodos Estadísticos$$cÁrea Estadís. Investig. Opera.
000118975 773__ $$g29, 3 (2022), 655–676$$pEnviron. ecol. stat.$$tENVIRONMENTAL AND ECOLOGICAL STATISTICS$$x1352-8505
000118975 8564_ $$s1202185$$uhttps://zaguan.unizar.es/record/118975/files/texto_completo.pdf$$yVersión publicada
000118975 8564_ $$s1265823$$uhttps://zaguan.unizar.es/record/118975/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000118975 909CO $$ooai:zaguan.unizar.es:118975$$particulos$$pdriver
000118975 951__ $$a2024-03-18-15:17:40
000118975 980__ $$aARTICLE