Browsing by Author "Flores, Miguel"

Now showing items 1-8 of 8

    • A Nonparametric Bootstrap Method for Heteroscedastic Functional Data 

      Fernández-Casal, Rubén; Castillo-Páez, Sergio; Flores, Miguel (Springer, 2024-03)
      [Absctract]: The objective is to provide a nonparametric bootstrap method for functional data that consists of independent realizations of a continuous one-dimensional process. The process is assumed to be nonstationary, ...

    • Bootstrap-LOCI data mining methodology for anomaly detection in buildings energy efficiency 

      Tobar, Andrés; Flores, Miguel; Castillo-Páez, Sergio; Naya, Salvador; Zaragoza, Sonia; Tarrío-Saavedra, Javier (Elsevier, 2023-11)
      [Abtract]: An automated methodology is proposed to identify anomalies in buildings’ HVAC systems, through Local Correlation Integral (LOCI) algorithm, improved by Bootstrap to obtain a rule from its score distribution. ...

    • 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. ...

    • Constructing a Control Chart Using Functional Data 

      Flores, Miguel; Naya, Salvador; Fernández-Casal, Rubén; Zaragoza, Sonia; Raña, Paula; Tarrío-Saavedra, Javier (MDPI AG, 2020-01-02)
      [Abstract] This study proposes a control chart based on functional data to detect anomalies and estimate the normal output of industrial processes and services such as those related to the energy efficiency domain. Companies ...

    • Functional extensions of Mandel's h and k statistics for outlier detection in interlaboratory studies 

      Flores, Miguel; Tarrío-Saavedra, Javier; Fernández-Casal, Rubén; Naya, Salvador (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 ...

    • Local Correlation Integral Approach for Anomaly Detection Using Functional Data 

      Sosa, Jorge; Flores, Miguel; Naya, Salvador; Tarrío-Saavedra, Javier (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 ...

    • Predicting rainfall and irrigation requirements of corn in Ecuador 

      Flores, Miguel; Llambo, Ángel; Loza, Danilo; Naya, Salvador; Tarrío-Saavedra, Javier (Elsevier Ltd, 2023-08)
      [Abstract]: This work is a case study whose objective is prediction of irrigation needs of corn crops in different regions of Ecuador; being this a fundamental basic food for the country's economy, as in the remaining ...

    • Statistical Quality Control with the qcr Package 

      Flores, Miguel; Fernández-Casal, Rubén; Naya, Salvador; Tarrío-Saavedra, Javier (Technische Universitaet Wien, 2021)
      [Abstract] The R package qcr for Statistical Quality Control (SQC) is introduced and described. It includes a comprehensive set of univariate and multivariate SQC tools that completes and increases the SQC techniques ...