BOOTSTRAP AND PERMUTATION TESTS OF INDEPENDENCE FOR POINT PROCESSES

作者：Albert Melisande^*; Bouret Yann; Fromont Magalie; Reynaud Bouret Patricia

来源：Annals of Statistics, 2015, 43(6): 2537-2564.

DOI：10.1214/15-AOS1351

• Independence test
• U-statistics
• point processes
• bootstrap
• randomization
• permutation
• neuroscience
• spike train analysis

Motivated by a neuroscience question about synchrony detection in spike train analysis, we deal with the independence testing problem for point processes. We introduce nonparametric test statistics, which are resealed general U-statistics, whose corresponding critical values are constructed from bootstrap and randomization/permutation approaches, making as few assumptions as possible on the underlying distribution of the point processes. We derive general consistency results for the bootstrap and for the permutation w.r.t. Wasserstein's metric, which induces weak convergence as well as convergence of second-order moments. The obtained bootstrap or permutation independence tests are thus proved to be asymptotically of the prescribed size, and to be consistent against any reasonable alternative. A simulation study is performed to illustrate the derived theoretical results, and to compare the performance of our new tests with existing ones in the neuroscientific literature.

• 出版日期2015-12