Nonparametric density estimation for intentionally corrupted functional data

Nonparametric Functional Data Analysis through Bayesian Density Estimation

In many modern experimental settings, observations are obtained in the form of functions, and interest focuses on inferences on a collection of such functions. Some examples are conductivitytemperature-depth (CTD) data in oceanography, dose-response models in epidemiology and time-course microarray experiments in biology and medicine. In this paper we propose a hierarchical model that allows us...

Functional data clustering via piecewise constant nonparametric density estimation

In this paper, we present a novel way of analyzing and summarizing a collection of curves, based on piecewise constant density estimation. The curves are partitioned into clusters, and the dimensions of the curves points are discretized into intervals. The cross-product of these univariate partitions forms a data grid of cells, which represents a nonparametric estimator of the joint density of ...

Nonparametric Regression Estimation under Kernel Polynomial Model for Unstructured Data

The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framewo...

Workshop on Nonparametric Estimation and Functional data

Sequential nonparametric density estimation