Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1144524 | Journal of the Korean Statistical Society | 2016 | 18 Pages |
Abstract
A unified framework to analyse multivariate kernel estimators of distribution and survival functions is introduced, before turning our attention to receiver operating characteristic (ROC) curves. These are well-established visual analytic tools for univariate data samples, though their generalisation to multivariate data has been limited. Since non-parametric multivariate kernel smoothing methods possess excellent visualisation properties, they serve as a solid basis for their estimation. With optimal data-based bandwidth matrix selectors, we demonstrate that they possess suitable properties for exploratory data analysis of simulated and experimental data.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Tarn Duong,