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Nonparametric forecasting in time series: a comparative study
(Taylor & Francis, 2007)
The problem of predicting a future value of a time series is considered in this
paper. If the series follows a stationary Markov process, this can be done
by nonparametric estimation of the autoregression function. Two ...
Bandwidth selection for statistical matching and prediction
(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 ...
Analysis of interval‐grouped data in weed science: The binnednp Rcpp package
(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). ...
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 ...
Comments on: Nonparametric estimation in mixture cure models with covariates
(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 ...
Modeling the Number of People Infected With SARS-COV-2 From Wastewater Viral Load in Northwest Spain
(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 ...
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 ...
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 ...
Automatic detection of defective crankshafts by image analysis and supervised classification
(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 ...
Kernel distribution estimation for grouped data
(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 ...