Modelización, Optimización e Inferencia Estadística (MODES)
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Effectiveness of non-pharmaceutical interventions in nine fields of activity to decrease SARS-CoV-2 transmission (Spain, September 2020–May 2021)
(Frontiers Media S.A., 2023)[Abstract]: Background: We estimated the association between the level of restriction in nine different fields of activity and SARS-CoV-2 transmissibility in Spain, from 15 September 2020 to 9 May 2021. Methods: A stringency ... -
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 ... -
Small area estimation of average compositions under multivariate nested error regression models
(Springer Science and Business Media Deutschland GmbH, 2023)[Abstract]: This paper investigates the small area estimation of population averages of unit-level compositional data. The new methodology transforms the compositions into vectors of Rm and assumes that the vectors follow ... -
Hard and soft clustering of categorical time series based on two novel distances with an application to biological sequences
(Elsevier, 2023)[Abstract]: Two novel distances between categorical time series are introduced. Both of them measure discrepancies between extracted features describing the underlying serial dependence patterns. One distance is based on ... -
Local Correlation Integral Approach for Anomaly Detection Using Functional Data
(MDPI, 2023-02-06)[Abstract]: The present work develops a methodology for the detection of outliers in functional data, taking into account both their shape and magnitude. Specifically, the multivariate method of anomaly detection called ...
