We develop a "plug-in" kernel estimator for the differential entropy that is consistent even if the kernel width tends to zero as quickly as 1/N, where N is the number of...
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...
We evaluate probability density functions of diffusivity measures in DTI fiber tracts as biomarkers. For this, we estimate univariate and bivariate densities, such as joint probabi...
Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density esti...
Laura M. Smith, Matthew S. Keegan, Todd Wittman, G...
This paper presents a kernel density estimation method by means of real-coded crossovers. Estimation of density algorithms (EDAs) are evolutionary optimization techniques, which d...