Listar Modelización, Optimización e Inferencia Estadística (MODES) por autor "Cao, Ricardo"

Mostrando ítems 1-20 de 27

    • A cardiotoxicity dataset for breast cancer patients 

      Piñeiro Lamas, Beatriz; López-Cheda, Ana; Cao, Ricardo; Ramos-Alonso, Laura; González-Barbeito, Gabriel; Barbeito Caamaño, Cayetana; Bouzas-Mosquera, Alberto (Nature Research, 2023)
      [Abstract] This dataset is a result of the collaboration between the University of A Coruña and the University Hospital of A Coruña. It contains information about 531 women diagnosed with HER2+ breast cancer, treated with ...

    • A Doubly Smoothed PD Estimator in Credit Risk 

      Peláez, Rebeca; Cao, Ricardo; Vilar, Juan M. (MDPI AG, 2020-09-01)
      [Abstract] In this work a doubly smoothed probability of default (PD) estimator is proposed based on a smoothed version of the survival Beran’s estimator. The asymptotic properties of both the smoothed survival and PD ...

    • Analysis of interval‐grouped data in weed science: The binnednp Rcpp package 

      Barreiro-Ures, Daniel; Francisco-Fernández, Mario; Cao, Ricardo; Fraguela, Basilio B.; Doallo, Ramón; González-Andújar, José Luis; Reyes, Miguel (John Wiley & Sons Ltd., 2019-09-13)
      [Abstract] Weed scientists are usually interested in the study of the distribution and density functions of the random variable that relates weed emergence with environmental indices like the hydrothermal time (HTT). ...

    • Automatic detection of defective crankshafts by image analysis and supervised classification 

      Remeseiro, Beatriz; Tarrío-Saavedra, Javier; Francisco-Fernández, Mario; Penedo, Manuel; Naya, Salvador; Cao, Ricardo (2019)
      [Abstract]: A crankshaft is a mechanical component of an engine that performs a conversion of an alternative movement of a piston in a rotational motion of a shaft. It is a critical part and one of the most expensive of ...

    • Bagging cross-validated bandwidths with application to big data 

      Barreiro-Ures, Daniel; Cao, Ricardo; Francisco-Fernández, Mario; Hart, Jeffrey D. (2021)
      Hall & Robinson (2009) proposed and analysed the use of bagged cross-validation to choose the band-width of a kernel density estimator. They established that bagging greatly reduces the noise inherent in ordinary ...

    • Bandwidth Selection for Prediction in Regression 

      Barbeito, Inés; Cao, Ricardo; Sperlich, Stefan (M D P I AG, 2019-08-05)
      [Abstract] There exist many different methods to choose the bandwidth in kernel regression. If, however, the target is regression based prediction for samples or populations with potentially different distributions, then ...

    • Bandwidth selection for statistical matching and prediction 

      Barbeito Cal, Inés; Cao, Ricardo; Sperlich, Stephan (Springer, 2022)
      [Abstract]: While there exist many bandwidth selectors for estimation, bandwidth selection for statistical matching and prediction has hardly been studied so far. We introduce a computationally attractive selector for ...

    • Big-But-Biased Data Analytics for Air Quality 

      Borrajo, Laura; Cao, Ricardo (MDPI AG, 2020-09-22)
      [Abstract] Air pollution is one of the big concerns for smart cities. The problem of applying big data analytics to sampling bias in the context of urban air quality is studied in this paper. A nonparametric estimator ...

    • Bootstrap Bandwidth Selection and Confidence Regions for Double Smoothed Default Probability Estimation 

      Peláez, Rebeca; Cao, Ricardo; Vilar, Juan M. (MDPI, 2022)
      [Abstract] For a fixed time, t, and a horizon time, b, the probability of default (PD) measures the probability that an obligor, that has paid his/her credit until time t, runs into arrears not later that time t+b. This ...

    • Bootstrap Selector for the Smoothing Parameter of Beran’s Estimator 

      Peláez, Rebeca; Cao, Ricardo; Vilar, Juan M. (MDPI, 2021)
      [Abstract] This work proposes a resampling technique to approximate the smoothing parameter of Beran’s estimator. It is based on resampling by the smoothed bootstrap and minimising the bootstrap approximation of the mean ...

    • Comments on: Nonparametric estimation in mixture cure models with covariates 

      Cao, Ricardo (Springer Science and Business Media Deutschland GmbH, 2023)
      [Abstract]: This paper discusses the invited paper by López-Cheda, Peng and Jácome on nonparametric mixture cure models with covariates. An alternative estimation procedure is proposed in this context. The situation when ...

    • Computationally Efficient Bootstrap Expressions for Bandwidth Selection in Nonparametric Curve Estimation 

      Barbeito Cal, Inés; Cao, Ricardo (M D P I AG, 2018-09-17)
      [Abstract] Bootstrap methods are used for bandwidth selection in: (1) nonparametric kernel density estimation with dependent data (smoothed stationary bootstrap and smoothed moving blocks bootstrap), and (2) nonparametric ...

    • 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 ...

    • Cure models to estimate time until hospitalization due to COVID-19 

      Pedrosa-Laza, Maria; López-Cheda, Ana; Cao, Ricardo (Springer Nature, 2022-01)
      [Abstract]: A short introduction to survival analysis and censored data is included in this paper. A thorough literature review in the field of cure models has been done. An overview on the most important and recent ...

    • Effectiveness of non-pharmaceutical interventions in nine fields of activity to decrease SARS-CoV-2 transmission (Spain, September 2020–May 2021) 

      Barbeito, Inés; Precioso, Daniel; Sierra, María José; Vegas-Azcárate, Susana; Fernández-Balbuena, Sonia; Vitoriano, Begoña; Gómez-Ullate, David; Cao, Ricardo; Monge, Susana (Frontiers Media S.A., 2023)
      [Abstract]: Background: We estimated the association between the level of restriction in nine different fields of activity and SARS-CoV-2 transmissibility in Spain, from 15 September 2020 to 9 May 2021. Methods: A stringency ...

    • Estimating Lengths-Of-Stay of Hospitalized COVID-19 Patients Using a Non-parametric Model: A Case Study in Galicia (Spain) 

      López-Cheda, Ana; Cao, Ricardo; De Salazar, Pablo M.; Jácome, M. A. (Cambridge University Press, 2021)
      [Abstract] Estimating the lengths-of-stay (LoS) of hospitalised COVID-19 patients is key for predicting the hospital beds’ demand and planning mitigation strategies, as overwhelming the healthcare systems has critical ...

    • Introducción a la simulación y a la teoría de colas 

      Cao, Ricardo (Netbiblo, 2002)
      [Resumen] Esta Obra cubre los contenidos basicos de las materias: Simulacion y Teoria de Colas; son de indudable interes en titulaciones universitarias como la Ingenieria Informatica o de Telecomunicaciones y resultando ...

    • Kernel distribution estimation for grouped data 

      Reyes, Miguel; Francisco-Fernández, Mario; Cao, Ricardo; Barreiro-Ures, Daniel (Institut d'Estadística de Catalunya, 2019)
      [Abstract]: Interval-grouped data appear when the observations are not obtained in continuous time, but monitored in periodical time instants. In this framework, a nonparametric kernel distribution esti- mator is proposed ...

    • Modeling the Number of People Infected With SARS-COV-2 From Wastewater Viral Load in Northwest Spain 

      Vallejo, J. A.; Trigo Tasende, Noelia; Rumbo-Feal, Soraya; Conde-Pérez, Kelly; López-Oriona, Ángel; Barbeito, Inés; Vaamonde, Manuel; Tarrío-Saavedra, Javier; Reif López, Rubén; Ladra, Susana; Rodiño-Janeiro, Bruno Kotska; Nasser-Ali, Mohammed; Cid, Ángeles; Veiga, María Carmen; Acevedo, Antón; Lamora, Carlos; Bou, Germán; Cao, Ricardo; Poza, Margarita (Elsevier, 2022)
      [Abstract] The quantification of the SARS-CoV-2 RNA load in wastewater has emerged as a useful tool to monitor COVID–19 outbreaks in the community. This approach was implemented in the metropolitan area of A Coruña (NW ...

    • Nonlinear regression model checking via local polynomial smoothing 

      Cao, Ricardo; Naya, Salvador (2007-05-14)
      A goodness-of-fitt test statistic for nonlinear regression models based on local polynomial estimation is proposed in this paper. The criterion used to construct the test is the distance between the parametric fitt and the ...