In this paper we study the problem of bivariate density estimation. The aim is to find a density function with the smallest number of local extreme values which is adequate with ...
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...
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density ...