We consider kernel density estimation when the observations are contaminated by measurement errors. It is well known that the success of kernel estimators ...
Apr 1, 2011 · We consider kernel density estimation when the observations are contaminated by measurement errors. It is well-known that the success of ...
This work considers kernel density estimation when the observations are contaminated by measurement errors and suggests several data-driven local bandwidth ...
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Abstract We consider kernel density estimation when the observations are contaminated by measurement errors. It is well-known that the success of kernel ...
We consider kernel density estimation when the observations are contaminated by measurement errors. It is well-known that the success of kernel estima.
Feb 28, 2014 · I would apply the variable bandwidth kernel density estimator, e.g. Local bandwidth selectors for deconvolution kernel density estimation ...
Local bandwidth selectors for deconvolution kernel density estimation · A. AchilleosA. Delaigle. Computer Science, Mathematics. Statistics and Computing. 2011.
Apr 12, 2016 · The article Local bandwidth selectors for deconvolution kernel density estimation mentioned in this answer seems to address this issue, but ...
The selectors are a refinement of the simple normal reference bandwidth selector, which is obtained by parametrically estimating the approximated mean ...
Dec 7, 2020 · In this paper, we develop density estimation methods using smoothing kernels. We use the framework of deconvoluting kernel density estimators to ...