pyevidence: practical evidence theory
Introduces pyevidence, a Python library for practical implementation of Dempster-Shafer evidence theory, addressing computational challenges.
Introduces pyevidence, a Python library for practical implementation of Dempster-Shafer evidence theory, addressing computational challenges.
Compares Satterthwaite, Liu, and leading-term approximations for tail probabilities of weighted sums of chi-squared variables in high-dimensional genomic data.
Explores valid reasons for using simplified assumptions like 'spherical cows' in statistical modeling and theoretical work.
Argues for the importance of statistical theory in data science, using examples from medical research to show where abstract theory solved practical problems.