
handle: 2183/46429
[Resumen]: La detección de valores atípicos en series de tiempo constituye una tarea de gran relevancia para asegurar la validez y la fiabilidad de los análisis. En el presente trabajo se lleva a cabo una evaluación, a través de diferentes escenarios de simulación, de múltiples combinaciones de algoritmos de detección de valores atípicos en series temporales.Este estudio de simulación posibilita la identificación de los métodos más eficientes y proporciona una base sólida para el análisis de la presencia de valores atípicos en series de tiempo con datos reales.
[Abstract]: The detection of outliers in time series constitutes a task of great importance to ensure the validity and reliability of analyses. In this study, an evaluation is carried out, through different simulation scenarios, of multiple combinations of algorithms for outlier detection in time series. This simulation study enables the identification of the most efficient methods and provides a solid foundation for the analysis of the presence of outliers in time series with real data.
Traballo fin de grao (UDC.FIC). Ciencia e enxeñaría de datos. Curso 2024/2025
Modelos ARIMA, Outlier detection in time series, Evaluation metrics, Time series modeling, Detección de atípicos en series temporales, Métricas de evaluación, Modelización de series de tiempo, ARIMA Models
Modelos ARIMA, Outlier detection in time series, Evaluation metrics, Time series modeling, Detección de atípicos en series temporales, Métricas de evaluación, Modelización de series de tiempo, ARIMA Models
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