This article gives ideas for developing statistics software which can work without user intervention. Some popular methods of bandwidth selection for kernel density estimation (the...
We present two solutions for the scale selection problem in computer vision. The rst one is completely nonparametric and is based on the the adaptive estimation of the normalized ...
We consider kernel density estimation when the observations are contaminated by measurement errors. It is well known that the success of kernel estimators depends heavily on the c...
Given angular data 1, . . . , n [0, 2) a common objective is to estimate the density. In the case that a kernel estimator is used, bandwidth selection is crucial to the performan...
: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...