For the purpose of comparing different nonparametric density estimators, Wegman (J. Statist. Comput. Simulation 1 225-245) introduced an empirical error criterion. In a recent paper by Hall (Stochastic Process. Appl. 13 11-25) it is shown that this empirical error criterion converges to the mean...

This paper deals with a quite general nonparametric statistical curve estimation setting. Special cases include estimation or probability density functions, regression functions, and hazard functions. The class of "fractional delta sequence estimators" is defined and treated here. This class...

This article discusses a study of cell images in cell culture biology from an object-oriented point of view. The motivation of this research is to develop a statistical approach to cell image analysis that better supports the automated development of stem cell growth media. A major hurdle in...

Driven by network intrusion detection, we propose a MultiResolution Anomaly Detection (MRAD) method, which effectively utilizes the multiscale properties of Internet features and network anomalies. In this paper, several theoretical properties of the MRAD method are explored. A major new result...

In this paper, we extend SiZer (SIgnificant ZERo crossing of the derivatives) to dependent data for the purpose of goodness-of-fit tests for time series models. Dependent SiZer compares the observed data with a specific null model being tested by adjusting the statistical inference using an...

High-dimension, low-small-sample size datasets have different geometrical properties from those of traditional low-dimensional data. In their asymptotic study regarding increasing dimensionality with a fixed sample size, Hall et al. (2005) showed that each data vector is approximately located on...

We study a discriminant direction vector that generally exists only in high-dimension, low sample size settings. Projections of data onto this direction vector take on only two distinct values, one for each class. There exist infinitely many such directions in the subspace generated by the data;...