Game-theoretic statistics and safe anytime-valid inference
Safe anytime-valid inference (SAVI) provides measures of statistical evidence and certainty—
e-processes for testing and confidence sequences for estimation—that remain valid at all …
e-processes for testing and confidence sequences for estimation—that remain valid at all …
Estimating means of bounded random variables by betting
We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical
problem of estimating a bounded mean. Our approach generalizes and improves on the …
problem of estimating a bounded mean. Our approach generalizes and improves on the …
E-values: Calibration, combination and applications
E-values: Calibration, combination and applications Page 1 The Annals of Statistics 2021, Vol.
49, No. 3, 1736–1754 https://doi.org/10.1214/20-AOS2020 © Institute of Mathematical Statistics …
49, No. 3, 1736–1754 https://doi.org/10.1214/20-AOS2020 © Institute of Mathematical Statistics …
Admissible anytime-valid sequential inference must rely on nonnegative martingales
Confidence sequences, anytime p-values (called p-processes in this paper), and e-
processes all enable sequential inference for composite and nonparametric classes of …
processes all enable sequential inference for composite and nonparametric classes of …
Likelihood ratio confidence sets for sequential decision making
Certifiable, adaptive uncertainty estimates for unknown quantities are an essential
ingredient of sequential decision-making algorithms. Standard approaches rely on problem …
ingredient of sequential decision-making algorithms. Standard approaches rely on problem …
False discovery rate control with e-values
E-values have gained attention as potential alternatives to p-values as measures of
uncertainty, significance and evidence. In brief, e-values are realized by random variables …
uncertainty, significance and evidence. In brief, e-values are realized by random variables …
Derandomised knockoffs: leveraging e-values for false discovery rate control
Abstract Model-X knockoffs is a flexible wrapper method for high-dimensional regression
algorithms, which provides guaranteed control of the false discovery rate (FDR). Due to the …
algorithms, which provides guaranteed control of the false discovery rate (FDR). Due to the …
Testing exchangeability: Fork-convexity, supermartingales and e-processes
Suppose we observe an infinite series of coin flips X 1, X 2,…, and wish to sequentially test
the null that these binary random variables are exchangeable. Nonnegative …
the null that these binary random variables are exchangeable. Nonnegative …
Improved regret bounds of (multinomial) logistic bandits via regret-to-confidence-set conversion
Logistic bandit is a ubiquitous framework of modeling users' choices, eg, click vs. no click for
advertisement recommender system. We observe that the prior works overlook or neglect …
advertisement recommender system. We observe that the prior works overlook or neglect …
A Discussion of" A Note on Universal Inference" by Tse and Davison.
The article discusses the concept of universal inference (UI) and its limitations in problems
with high-dimensional nuisance parameters. It introduces a modification called the quasi …
with high-dimensional nuisance parameters. It introduces a modification called the quasi …