GI-MODES - Artigos: Envíos recentes

Mostrando ítems 1-5 de 143

    • Bootstrap prediction regions for daily curves of electricity demand and price using functional data 

      Peláez, Rebeca; Aneiros Pérez, Germán; Vilar, Juan M. (Elsevier, 2024-11)
      [Abstract]: The aim of this paper is to compute one-day-ahead prediction regions for daily curves of electricity demand and price. Three model-based procedures to construct general prediction regions are proposed, all of ...

    • Conditional likelihood based inference on single-index models for motor insurance claim severity 

      Bolancé Losilla, Catalina; Cao, Ricardo; Guillén, Montserrat (Institut d'Estadistica de Catalunya, 2024)
      [Abstract]: Prediction of a traffc accident cost is one of the major problems in motor insurance. To identify the factors that infuence costs is one of the main challenges of actuarial modelling. Telematics data about ...

    • On benefits of cooperation under strategic power 

      Fiestras Janeiro, María Gloria; García-Jurado, Ignacio; Meca Martínez, Ana; Mosquera Rodríguez, Manuel Alfredo (Springer, 2020-05)
      [Abstract]: We introduce a new model involving TU-games and exogenous structures. Specifically, we consider that each player in a population can choose an element in a strategy set and that, for every possible strategy ...

    • A heuristic approach to the task planning problem in a home care business 

      Méndez-Fernández, Isabel; Lorenzo Freire, Silvia; García-Jurado, Ignacio; Costa, Julián; Carpente, Luisa (Springer, 2020-12)
      [Abstract]: In this paper, we study a task scheduling problem in a home care business. The company has a set of supervisors in charge of scheduling the caregivers’ weekly plans. This can be a time-consuming task due to the ...

    • Bootstrap-based statistical inference for linear mixed effects under misspecifications 

      Reluga, Katarzyna; Lombardía, María José; Sperlich, Stefan (Elsevier, 2024)
      [Abstract]: Linear mixed effects are considered excellent predictors of cluster-level parameters in various domains. However, previous research has demonstrated that their performance is affected by departures from model ...