(2018). Kernel-based tests for joint independence. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 80(1):5-31. 1Pfister, N., Buhlmann, P., Scholkopf, B. and Peters, J. (2017) Kernel-based tests for joint independence. Journal of the Royal Statistical ...
Kernel-based Tests for Joint Independence estimate of dHSIC, we define three different non-parametric hypothesis tests: a permutation test, a bootstrap test and a test based on a Gamma ... N Pfister,P Bühlmann,B Sch?Lkopf,... - 《Journal of the Royal Statistical Society》 被引量: 32...
Testing for CI is much more di?cult than that for unconditional independence (Bergsma, 2004). For CI tests, traditional methods either focus on the discrete case, or impose simplifying assumptions to deal with but overlapping subsets of Z ; even if X ⊥⊥ Y |Z , it is impossible to ?
(2018). Kernel-based tests for joint inde- pendence. J. R. Stat. Soc. Ser. B. Stat. Methodol., 80(1):5-31.Pfister, N., Bu¨hlmann, P., Sch¨olkopf, B. and Peters, J. (2018), Kernel-based tests for joint independence, J. R. Stat. Soc. B, 80, 5-31....
This is important in many applications, for example in feature selection. The estimator is consistent, robust to outliers, and uses rank statistics only. We derive upper bounds on the convergence rate and propose independence tests too. We illustrate the theoretical contributions through a series of...
The tests and their results are presented in the following subsections. In each test, we generate an ensemble drawn from the prior, apply the three filters above to the same prior ensemble, and use the Kolmogorov–Smirnov (KS; [16]) test on the null hypothesis that the analysis ensemble ...