Please use this identifier to cite or link to this item:
https://elib.bsu.by/handle/123456789/93494| Title: | Testing of Independency for High-Dimensional Data |
| Authors: | Radavicius, M. Jakimauskas, G. Susinskas, J. |
| Keywords: | ЭБ БГУ::ОБЩЕСТВЕННЫЕ НАУКИ::Информатика |
| Issue Date: | 2007 |
| Publisher: | Minsk: BSU |
| Abstract: | A simple, data-driven and computationally efficient procedure for testing independence of variables in high-dimension data is proposed. The procedure is based on interpretation of testing goodness-of-fit as the classification problem, a special sequential partition procedure, elements of sequential testing, resampling and randomization. Monte Carlo simulations are used to assess the performance of the procedure. |
| URI: | http://elib.bsu.by/handle/123456789/93494 |
| Appears in Collections: | Section 2. MULTIVARIATE ANALYSIS AND DESIGN OF EXPERIMENTS |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.