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Nonparametric covariate hypothesis tests for the cure rate in mixture cure models
(John Wiley & Sons, 2020-06)
[Abstract]: In lifetime data, like cancer studies, there may be long term survivors, which lead to heavy censoring at the end of the follow-up period. Since a standard survival model is not appropriate to handle these data, ...
Big-But-Biased Data Analytics for Air Quality
(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 ...
Bagging cross-validated bandwidths with application to big data
(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 ...
Nonparametric estimation of the probability of default with double smoothing
(Institut d'Estadistica de Catalunya, 2021)
[Abstract]: In this paper, a general nonparametric estimator of the probability of default is proposed and studied. It is derived from an estimator of the conditional survival function for censored data obtained with a ...
Estimating Lengths-Of-Stay of Hospitalized COVID-19 Patients Using a Non-parametric Model: A Case Study in Galicia (Spain)
(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 ...