This short course will provide an overview of non-parametric statistical techniques. The course will first describe what non-parametric statistics are, when they should be used, and their advantages ...

This article extends recent results [Scand. J. Statist. 28 (2001) 699] about exact non-parametric inferences based on order statistics with progressive type-II censoring. The extension lies in that ...

The paper develops non-parametric methods based on contact intervals for the analysis of infectious disease data. The contact interval from person i to person j is the time between the onset of ...

We use influence functions as a basic tool to study unconditional nonparametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence.

The frequency of left-handedness in the general population is around 11%. Both environmental and genetic models have been proposed to explain the aetiology of human handedness. The majority of genetic ...

A non-parametric method for paleohydrologic reconstruction (NPP) of streamflows using tree-ring chronologies is developed. The method uses pattern matching of chronologies in EOF-space (Empirical ...

Nonparametric regression for functional data provides a flexible statistical framework for modelling relationships between a scalar response and predictors that are inherently functional in nature.

In the post-parametric era, one key challenge for architectural design is the acquisition, processing, and integration of data. Designers already have an enormous amount of computable data from ...