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 ...

Abstract: Streamflow disaggregation techniques are used to distribute a single aggregate flow value to multiple sites in both space and time while preserving distributional statistics (i.e., mean, ...

We provide novel, high-order accurate methods for non-parametric inference on quantile differences between two populations in both unconditional and conditional settings. These quantile differences ...

Multiple event data are frequently encountered in medical follow-up, engineering and other applications when the multiple events are considered as the major outcomes. They may be repetitions of the ...

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 ...