In Statistical Comparisons of Classifiers over Multiple Data Sets (p. 12) Janez Demsar suggests to use the Bonferroni-Dunn test as a post-hoc test after the null hypothesis of an initial Friedman test was rejected.
Questions:
- Friedman test is non-parametric. May one use a parametric test as a post-hoc test (e.g., paired t-test with Bonferroni adjustment)?
- Is the Wilcoxon signed-rank test with Bonferroni adjustment also an appropriate post-hoc test in this case?
- The paper does not suggest pairwise comparisons of all groups if one wants to test a new algorithm against existing baselines. Instead, one should only compare the new algorithm (control) to the existing ones. How would Bonferroni adjustment work in this case? Still by dividing by the number of tests that were conducted?