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This paper introduces pragmatic hypotheses and relates this concept to the spiral of scientific evolution. Previous works determined a …

The quantification problem consists of determining the prevalence of a given label in a target population. However, one often has access to the labels in a sample from the training population but not in the target population. A common assumption in this situation is that of prior probability shift, that is, once the labels are known, the distribution of the features is the same in the training and target populations. In this paper, we derive a new lower bound for the risk of the quantification problem under the prior shift assumption. Using a weaker version of the prior shift assumption, which can be tested, we show that ratio estimators can be used to build confidence intervals for the quantification problem.

We propose two Bayesian multinomial-Dirichlet models to predict the final outcome of football (soccer) matches and compare them to …

Detecting trends in population size fluctuations is a major focus in ecology, evolution, and conservation biology. Populations of …

The association between hypertension and frailty syndrome in older adults remains unclear. There is scarce information about the …