Statistical uncertainty in data—or random error in a measurement—particularly when it is used to inform funding and policies, can lead to a variety of issues ...

Uncertain regression models represent an evolving paradigm in statistical analysis, designed to address the challenges posed by imprecise observations. Traditional regression techniques typically ...

The capacity for assessing the degree of uncertainty in the environment relies on estimating statistics of temporally unfolding inputs. This, in turn, allows calibration of predictive and bottom-up ...