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Charlier, Paindaveine, and Saracco (2014) recently introduced a nonparametric estimatorof conditional quantiles based on optimal quantization, but almost exclusively focused onits theoretical properties. In this paper, (i) we discuss its practical implementation (byproposing in particular a...
Persistent link: https://www.econbiz.de/10010892354
Motivated by the problem of setting prediction intervals in time seriesanalysis, this investigation is concerned with recovering a regression functionm(X_t) on the basis of noisy observations taking at random design pointsX_t.It is presumed that the corresponding observations are corrupted by...
Persistent link: https://www.econbiz.de/10010324657
Motivated by the problem of setting prediction intervals in time seriesanalysis, this investigation is concerned with recovering a regression functionm(X_t) on the basis of noisy observations taking at random design pointsX_t.It is presumed that the corresponding observations are corrupted by...
Persistent link: https://www.econbiz.de/10011302141
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This paper considers a wavelet method for the estimation of the density and hazard rate functions from randomly censored data. We establish the weak uniform consistency of the density and hazard rate estimators.
Persistent link: https://www.econbiz.de/10005137764
We propose a kernel-based multi-stage conditional median predictor for [alpha]-mixing time series of Markovian structure. Mean squared error properties of single-stage and multi-stage conditional medians are derived and discussed.
Persistent link: https://www.econbiz.de/10005137879