Resumen: The 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. Idioma: Inglés DOI: 10.1007/s10651-022-00539-2 Año: 2022 Publicado en: ENVIRONMENTAL AND ECOLOGICAL STATISTICS 29, 3 (2022), 655–676 ISSN: 1352-8505 Factor impacto JCR: 3.8 (2022) Categ. JCR: STATISTICS & PROBABILITY rank: 13 / 125 = 0.104 (2022) - Q1 - T1 Categ. JCR: MATHEMATICS, INTERDISCIPLINARY APPLICATIONS rank: 19 / 107 = 0.178 (2022) - Q1 - T1 Categ. JCR: ENVIRONMENTAL SCIENCES rank: 119 / 275 = 0.433 (2022) - Q2 - T2 Factor impacto CITESCORE: 4.0 - Environmental Science (Q2) - Mathematics (Q1) - Decision Sciences (Q2)