Report
Discussion of `Multiscale Fisher's Independence Test for Multivariate Dependence'
| العنوان: | Discussion of `Multiscale Fisher's Independence Test for Multivariate Dependence' |
|---|---|
| المؤلفون: | Schrab, Antonin, Jitkrittum, Wittawat, Szabó, Zoltán, Sejdinovic, Dino, Gretton, Arthur |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Statistics - Methodology, Computer Science - Machine Learning, Statistics - Applications, Statistics - Computation, Statistics - Machine Learning |
| الوصف: | We discuss how MultiFIT, the Multiscale Fisher's Independence Test for Multivariate Dependence proposed by Gorsky and Ma (2022), compares to existing linear-time kernel tests based on the Hilbert-Schmidt independence criterion (HSIC). We highlight the fact that the levels of the kernel tests at any finite sample size can be controlled exactly, as it is the case with the level of MultiFIT. In our experiments, we observe some of the performance limitations of MultiFIT in terms of test power. Comment: 8 pages |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2206.11142 |
| رقم الانضمام: | edsarx.2206.11142 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |