Global tests for quantile regression with applications in modeling distributions.
Konstantinos Konstantinou (Chalmers University of Technology & University of Gothenburg)
Abstract: In this talk, I will give an introduction to global tests for quantile regression, i.e., statistical tests allowing for simultaneous inference of the quantile regression process, with graphical interpretation. The proposed global quantile regression tests can determine not only if there is a difference, but it can also determine for which quantiles the difference is significant on the global significance level. The case where the effect of a factor (e.g., a categorical factor giving the group) on the distribution functions is of interest but confounded with other factors affecting the distributions is studied. An extensive simulation study is conducted to compare the global quantile regression tests with classical graphical tests based on the Kolmogorov-Smirnov test statistic. This is a joint work with Tomáš Mrkvička, Mari Myllymäki and Mikko Kuronen.
machine learningprobabilitystatistics theory
Audience: researchers in the discipline
Series comments: Gothenburg statistics seminar is open to the interested public, everybody is welcome. It usually takes place in MVL14 (http://maps.chalmers.se/#05137ad7-4d34-45e2-9d14-7f970517e2b60, see specific talk).
| Organizers: | Moritz Schauer*, Ottmar Cronie* |
| *contact for this listing |