Time-uniform, nonparametric, nonasymptotic confidence sequences
DOI10.1214/20-AOS1991zbMath1476.62170arXiv1810.08240OpenAlexW3148231156MaRDI QIDQ2039804
Jon D. McAuliffe, Jasjeet Sekhon, Aaditya Ramdas, Steven R. Howard
Publication date: 5 July 2021
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1810.08240
sequential probability ratio testexponential concentrationconfidence sequencematrix concentrationempirical-Bernstein bound
Martingales with discrete parameter (60G42) Nonparametric estimation (62G05) Random matrices (probabilistic aspects) (60B20) Nonparametric tolerance and confidence regions (62G15) Sample path properties (60G17) Random matrices (algebraic aspects) (15B52) Sequential estimation (62L12)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A Maximized Sequential Probability Ratio Test for Drug and Vaccine Safety Surveillance
- Concentration inequalities and moment bounds for sample covariance operators
- Test martingales, Bayes factors and \(p\)-values
- Freedman's inequality for matrix martingales
- Context tree selection: a unifying view
- Pseudo-maximization and self-normalized processes
- Exploration-exploitation tradeoff using variance estimates in multi-armed bandits
- Theory and applications of multivariate self-normalized processes
- Sequential analysis. Tests and confidence intervals
- A sequential clinical trial for testing \(p_1=p_2\)
- The expected sample size of some tests of power one
- Boundary crossing probabilities for sample sums and confidence sequences
- On confidence sequences
- A nonlinear renewal theory with applications to sequential analysis. I
- A nonlinear renewal theory with applications to sequential analysis II
- Random vectors in the isotropic position
- On the application of probability theory to agricultural experiments. Essay on principles. Section 9. Translated from the Polish and edited by D. M. Dąbrowska and T. P. Speed
- Self-normalized processes: exponential inequalities, moment bounds and iterated logarithm laws.
- Time-uniform Chernoff bounds via nonnegative supermartingales
- Weighted sums of certain dependent random variables
- Nonanticipating estimation applied to sequential analysis and changepoint detection
- Concentration Inequalities
- Concentration of Measure Inequalities in Information Theory, Communications, and Coding
- Discrete Sequential Boundaries for Clinical Trials
- Self-Normalized Processes
- Estimation Following Sequential Tests
- Incorporating scientific, ethical and economic considerations into the design of clinical trials in the pharmaceutical industry: a sequential approach
- Causal Inference for Statistics, Social, and Biomedical Sciences
- Concentration Inequalities for Sums and Martingales
- Probability Inequalities for Sums of Bounded Random Variables
- An Introduction to Matrix Concentration Inequalities
- ITERATED LOGARITHM INEQUALITIES
- CONFIDENCE SEQUENCES FOR MEAN, VARIANCE, AND MEDIAN
- PROBABILITY DISTRIBUTIONS RELATED TO THE LAW OF THE ITERATED LOGARITHM
- SOME FURTHER REMARKS ON INEQUALITIES FOR SAMPLE SUMS
- Forcing a sequential experiment to be balanced
- The Hartman-Wintner Law of the Iterated Logarithm for Martingales
- Statistical Methods Related to the Law of the Iterated Logarithm
- Boundary Crossing Probabilities for the Wiener Process and Sample Sums
- A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations
- Sequential Tests of Statistical Hypotheses