ListarModelización, Optimización e Inferencia Estadística (MODES) por tema "Outlier detection"
Mostrando ítems 1-3 de 3
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Functional extensions of Mandel's h and k statistics for outlier detection in interlaboratory studies
(Elsevier B.V., 2018-05-15)[Abstract]: Functional data analysis (FDA) alternatives, based on the classical Mandel h and k statistics, are proposed to identify the laboratories that supply inconsistent results in interlaboratory studies (ILS). ILS ... -
Machine learning for multivariate time series with the R package mlmts
(Elsevier B.V., 2023-06)[Abstract]: Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with univariate time series, multivariate time series have typically received much less attention. However, the ... -
Using robust FPCA to identify outliers in functional time series, with applications to the electricity market
(Institut d'Estadistica de Catalunya, 2016)[Abstract]: This study proposes two methods for detecting outliers in functional time series. Both methods take dependence in the data into account and are based on robust functional principal component analysis. One method ...