Modelización, Optimización e Inferencia Estadística (MODES): Envíos recentes
Mostrando ítems 1-5 de 141
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A Nonparametric Bootstrap Method for Heteroscedastic Functional Data
(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
(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
(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
(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
(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 ...
