Mostrando ítems 6-10 de 18

    • Installing Green Artificial Reefs: A Sustainable Challenge 

      Munín-Doce, Alicia; Castro-Santos, Laura; Carral Couce, Luis; Cartelle Barros, Juan José; Camba, C.; Tarrío-Saavedra, Javier (European Association for the Development of Renewable Energies, Environment and Power Quality (EA4EPQ),, 2021-09)
      [Abstract] Green Artificial Reefs (GARs) are marine structures to exploit sea resources in a sustainable way (produce food resources, improve the tourism, etc.). They should be installed on the seabed, process that is ...
    • Nonparametric Inference for Mixture Cure Model When Cure Information Is Partially Available 

      Clarence Safari, Wende; López-de-Ullibarri, Ignacio; Jácome, M. A. (MDPI, 2021)
      [Abstract] We introduce nonparametric estimators to estimate the conditional survival function, cure probability and latency function in the setting of a mixture cure model when the cure status is partially known. For the ...
    • Bootstrap Selector for the Smoothing Parameter of Beran’s Estimator 

      Peláez, Rebeca; Cao, Ricardo; Vilar, Juan M. (MDPI, 2021)
      [Abstract] This work proposes a resampling technique to approximate the smoothing parameter of Beran’s estimator. It is based on resampling by the smoothed bootstrap and minimising the bootstrap approximation of the mean ...
    • Robust Methods for Soft Clustering of Multidimensional Time Series 

      López-Oriona, Ángel; D'Urso, Pierpaolo; Vilar, José; Lafuente Rego, Borja Raúl (MDPI, 2021)
      [Abstract] Three robust algorithms for clustering multidimensional time series from the perspective of underlying processes are proposed. The methods are robust extensions of a fuzzy C-means model based on estimates of the ...
    • Case Study of Anomaly Detection and Quality Control of Energy Efficiency and Hygrothermal Comfort in Buildings 

      Eiras-Franco, Carlos; Flores, Miguel; Bolón-Canedo, Verónica; Zaragoza, Sonia; Fernández-Casal, Rubén; Naya, Salvador; Tarrío-Saavedra, Javier (2019)
      [Abstract] The aim of this work is to propose different statistical and machine learning methodologies for identifying anomalies and control the quality of energy efficiency and hygrothermal comfort in buildings. ...