• 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, ...

• Probability of default estimation in credit risk using mixture cure models 

  Peláez, Rebeca; Keilegom, Ingrid Van; Cao, Ricardo; Vilar, Juan M. (Elsevier, 2024-01)

  [Abstract]: An estimator of the probability of default (PD) in credit risk is proposed. It is derived from a nonparametric conditional survival function estimator based on cure models. Asymptotic expressions for the bias ...

• Cost-sensitive thresholding over a two-dimensional decision region for fraud detection 

  C-Rella, Jorge; Cao, Ricardo; Vilar, Juan M. (Elsevier B.V., 2024-02)

  [Absctract]: Credit fraud poses a challenging task in terms of detection. It can result in significant losses depending on the amount, so a cost-sensitive perspective needs to be taken. Classical approaches focus on ...

• Evaluating the impact of items and cooperation in inventory models with exemptable ordering costs 

  Fiestras Janeiro, María Gloria; García-Jurado, Ignacio; Meca Martínez, Ana; Mosquera Rodríguez, Manuel Alfredo (Elsevier B.V., 2024-03)

  [Absctract]: In this paper we introduce and analyse, from a game theoretical perspective, several multi-agent or multi-item continuous review inventory models in which the buyers are exempted from ordering costs if the ...

• 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 ...

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