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Bandwidth Selection for Prediction in Regression
(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 ...
Computationally Efficient Bootstrap Expressions for Bandwidth Selection in Nonparametric Curve Estimation
(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 ...
A Doubly Smoothed PD Estimator in Credit Risk
(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 ...
Bootstrap Selector for the Smoothing Parameter of Beran’s Estimator
(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 ...
Nonparametric Inference in Mixture Cure Models
(MDPI, 2018-09)
[Abstract]: A completely nonparametric method for the estimation of mixture cure models is proposed. Nonparametric estimators for the cure probability (incidence) and for the survival function of the uncured population ...