1 citations · 1 across the 4 of their papers we have counts for
4 papers
Robustness Quantification for Discriminative Models: a New Robustness Metric and its Application to Dynamic Classifier Selection
Rodrigo F. L. Lassance, Jasper De Bock
Among the different possible strategies for evaluating the reliability of individual predictions of classifiers, robustness quantification stands out as a method that evaluates how…
Nonparametric FBST for Validating Linear Models
Rodrigo F. L. Lassance, Julio M. Stern, Rafael B. Stern
The Full Bayesian Significance Test (FBST) possesses many desirable aspects, such as dismissing the need for hypotheses to have positive prior probability and providing a measure o…
PROTEST: Nonparametric Testing of Hypotheses Enhanced by Experts' Utility Judgements
Rodrigo F. L. Lassance, Rafael Izbicki, Rafael B. Stern
Instead of testing solely a precise hypothesis, it is often useful to enlarge it with alternatives that are deemed to differ from it negligibly. For instance, in a bioequivalence s…
REACT to NHST: Sensible conclusions to meaningful hypotheses
Rafael Izbicki, Luben M. C. Cabezas, Fernando A. B. Colugnatti +3
While Null Hypothesis Significance Testing (NHST) remains a widely used statistical tool, it suffers from several shortcomings in its common usage, such as conflating statistical a…