Bayesian Wilcoxon signed-rank test
The Bayesian Wilcoxon signed-rank test is a Bayesian nonparametric method for comparing two paired or related samples. Rather than returning a single p-value, it produces posterior probabilities that one condition is better, practically equivalent, or worse than the other, enabling richer and more interpretable inference for paired continuous or ordinal data without assuming normality.
Rekod sumber
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- Benavoli, A., Corani, G., & Mangili, F. (2014). Should we really use post-hoc tests based on mean-ranks? Journal of Machine Learning Research, 17(5), 1–10. · URL
- Benavoli, A., Corani, G., Demsar, J., & Zaffalon, M. (2017). Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis. Journal of Machine Learning Research, 18(77), 1–36. · URL
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