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Project

Imprecise random sequences and their statistical estimation.

We aim to develop a new framework for describing and estimating the uncertainty that is associated with data sequences. Our goals are similar to those of traditional statistics, but the crucial difference is that we intend to do drop the restrictive assumption that uncertainty should be described by a probability measure, resulting in methods that are more reliable and robust.

Date:1 Oct 2019 →  31 Oct 2020
Keywords:interval predictions, learning from data, randomness, Uncertainty, statistical estimation
Disciplines:Probability theory, Knowledge representation and reasoning, Statistics and numerical methods not elsewhere classified