Now showing items 1-5 of 5

    • Analyzing categorical time series with the R package ctsfeatures 

      López-Oriona, Ángel; Vilar, José (Elsevier B.V., 2024-03)
      [Absctract]: Time series data are ubiquitous nowadays. Whereas most of the literature on the topic deals with real-valued time series, categorical time series have received much less attention. However, the development of ...
    • Machine learning for multivariate time series with the R package mlmts 

      López-Oriona, Ángel; Vilar, José (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 ...
    • Ordinal Time Series Analysis with the R Package otsfeatures 

      López-Oriona, Ángel; Vilar, José (MDPI, 2023-06)
      [Abstract] The 21st century has witnessed a growing interest in the analysis of time series data. While most of the literature on the topic deals with real-valued time series, ordinal time series have typically received ...
    • ProjectManagement: an R Package for Managing Projects 

      Gonçalves-Dosantos, J.C.; García-Jurado, Ignacio; Costa, Julián (R Foundation for Statistical Computing, 2020)
      [Abstract]:Project management is an important body of knowledge and practices that comprises the planning, organisation and control of resources to achieve one or more pre-determined objectives. In this paper, we introduce ...
    • Scalable processing and autocovariance computation of big functional data 

      Brisaboa, Nieves R.; Cao, Ricardo; Paramá, José R.; Silva-Coira, Fernando (John Wiley & Sons, 2018)
      [Abstract]: This paper presents 2 main contributions. The first is a compact representation of huge sets of functional data or trajectories of continuous-time stochastic processes, which allows keeping the data always ...