70 citations · 165 across the 6 of their papers we have counts for
7 papers
Bagging cross-validated bandwidths with application to Big Data
Daniel Barreiro-Ures, Ricardo Cao, Mario Francisco Fernández +1
Hall and Robinson (2009) proposed and analyzed the use of bagged cross-validation to choose the bandwidth of a kernel density estimator. They established that bagging greatly reduc…
Cure models to estimate time until hospitalization due to COVID-19
Maria Pedrosa-Laza, Ana López-Cheda, Ricardo Cao
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 mo…
Nonparametric incidence estimation and bootstrap bandwidth selection in mixture cure models
Ana López-Cheda, Ricardo Cao, M. Amalia Jácome +1
A completely nonparametric method for the estimation of mixture cure models is proposed. A nonparametric estimator of the incidence is extensively studied and a nonparametric estim…
Nonparametric covariate hypothesis tests for the cure rate in mixture cure models
Ana López-Cheda, M. Amalia Jácome, Ingrid Van Keilegom +1
In lifetime data, like cancer studies, theremay be long term survivors, which lead to heavy censoring at the end of the follow-up period. Since a standard survival model is not app…
Nonparametric latency estimation for mixture cure models
Ana López-Cheda, M. Amalia Jácome, Ricardo Cao
A nonparametric latency estimator for mixture cure models is studied in this paper. An i.i.d. representation is obtained, the asymptotic mean squared error of the latency estimator…
Estimating lengths-of-stay of hospitalised COVID-19 patients using a non-parametric model: a case study in Galicia (Spain)
Ana López-Cheda, M. Amalia Jácome, Ricardo Cao +1
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 healt…