I'm really interested in how distributions are represented/approximated. I've learned about and will implement advanced sampling algorithms and perhaps find some ...

This week, we're coming into the big turn in the class, from probability theory to sampling theory. In the probability theory section of the course, we developed the *theoretically* **best** possible ...

This course focuses on the design and analysis of survey samples for finite populations. Topics covered include: non-probability and probability sampling, simple random sampling, stratified sampling, ...

Probability theory has long provided a rigorous framework for quantifying uncertainty, yet its extension to infinite sets introduces profound conceptual challenges and opportunities. Contemporary ...

Abstract: This paper proposes a new perspective on the relationship between the sampling and aliasing. Unlike the uniform sampling case, where the aliases are simply periodic replicas of the original ...

Imprecise probability theory provides a robust alternative to traditional probability by representing uncertainty through ranges or sets of values rather than single numerical estimates. This ...