9 citations · 29 across the 18 of their papers we have counts for
6 papers · 1 filter
Gaffke's confidence interval for the mean of bounded data is inadmissible but asymptotically efficient
Jiahao Ming, Aaditya Ramdas, Yi Shen +2
Given observations , Gaffke (2005) defined \[ K_n(\mathbf x)=\mathbb{P}_{\mathbf D}\!\left\{\sum_{i=1}^n x_iD_i\le 1\right\}, \qquad (D_0,D_1,\ldots,D_n)…
Post-Hoc Large-Sample Statistical Inference
Ben Chugg, Etienne Gauthier, Michael I. Jordan +2
We derive inferential procedures for large sample sizes that remain valid under data-dependent significance levels (so-called "post-hoc valid inference"). Classical statistical too…
Instance-Log-Optimality of Portfolio-Based E-Processes and their Sequential Hypothesis Tests
Ian Waudby-Smith, Ricardo Sandoval, Ricardo J. Sandoval +1
We consider the problem of sequential hypothesis testing using -processes. For a rich class of composite testing problems---which include bounded mean testing, equal mean testin…
Distribution-uniform anytime-valid sequential inference and the Robbins-Siegmund distributions
Ian Waudby-Smith, Edward H. Kennedy, Aaditya Ramdas
This paper develops a theory of distribution- and time-uniform asymptotics, culminating in the first large-sample anytime-valid inference procedures that are shown to be uniformly…
Time-uniform central limit theory and asymptotic confidence sequences
Ian Waudby-Smith, David Arbour, Ritwik Sinha +2
Confidence intervals based on the central limit theorem (CLT) are a cornerstone of classical statistics. Despite being only asymptotically valid, they are ubiquitous because they p…
Estimating means of bounded random variables by betting
Ian Waudby-Smith, Aaditya Ramdas
This paper derives confidence intervals (CI) and time-uniform confidence sequences (CS) for the classical problem of estimating an unknown mean from bounded observations. We presen…