Bootstrap Bandwidth Selection

Bootstrap Bandwidth Selection in Kernel Density Estimation from a Contaminated Sample*

Practical bandwidth selection in deconvolution kernel density estimation

Kernel estimation of a density based on contaminated data is considered and the important issue of how to choose the bandwidth parameter in practice is discussed. Some plug-in (PI) type of bandwidth selectors, which are based on non-parametric estimation of an approximation of the mean integrated squared error, are proposed. The selectors are a re4nement of the simple normal reference bandwidth...

Bootstrap Bandwidth and Kernel Order Selection for Density Weighted Averages

Abstract: Density weighted average is a nonparametric quantity expressed by expectation of a function of random variables with density weight. It is associated with parametric components of some semiparametric models, and we are concerned with an estimator of this quantity. Asymptotic properties of semiparametric estimators have been studied in econometrics since the end of 1980’s and it is now...

Available Link Bandwidth Based Network Selection in Multi-access Networks

In a heterogeneous wireless environment, one of the important aspects of seamless communication for ubiquitous computing is the dynamic selection of the best access network. The problem of access network selection has been addressed through various decision methods based on available network information. Available link bandwidth is one of the important information parameters, which can be used ...

Nonparametric Inference For Density Modes

We derive nonparametric confidence intervals for the eigenvalues of the Hessian at modes of a density estimate. This provides information about the strength and shape of modes and can also be used as a significance test. We use a datasplitting approach in which potential modes are identified using the first half of the data and inference is done with the second half of the data. To get valid co...