ListarModelización, Optimización e Inferencia Estadística (MODES) por tema "Functional data analysis"

Mostrando ítems 1-9 de 9

    • 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, ...

    • 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 ...

    • Erosive Degradation Study of Concrete Augmented by Mussel Shells for Marine Construction 

      Camba, C.; Mier, José; Carral Couce, Luis; Lamas, M.I.; Álvarez-Feal, José-Carlos; Díaz-Díaz, Ana-María; Tarrío-Saavedra, Javier (MDPI, 2021-10)
      [Abstract] This work proposes a green material for artificial reefs to be placed in Galicia (northwest Spain) taking into account the principles of circular economy and sustainability of the ecosystem. New concrete ...

    • Fast Algorithm for Impact Point Selection in Semiparametric Functional Models 

      Novo Díaz, Silvia; Aneiros Pérez, Germán; Vieu, Philippe (M D P I AG, 2019-07-31)
      [Abstract] A new sparse semiparametric functional model is proposed, which tries to incorporate the influence of two functional variables in a scalar response in a quite simple and interpretable way. One of the functional ...

    • 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 ...

    • 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 ...

    • Sparse Semi-Functional Partial Linear Single-Index Regression 

      Novo Díaz, Silvia; Aneiros Pérez, Germán; Vieu, Philippe (M D P I AG, 2018-09-17)
      [Abstract] The variable selection problem is studied in the sparse semi-functional partial linear model, with single-index type influence of the functional covariate in the response. The penalized least squares procedure ...

    • Using robust FPCA to identify outliers in functional time series, with applications to the electricity market 

      Vilar, Juan M.; Raña, Paula; Aneiros Pérez, Germán (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 ...