| Why are p-Values Controversial? TA Kuffner, SG Walker The American Statistician 73 (1), 1-3, 2019 | 60 | 2019 |
| Post-selection inference AK Kuchibhotla, JE Kolassa, TA Kuffner Annual Review of Statistics and Its Application 9 (1), 505-527, 2022 | 41 | 2022 |
| Bayes factor consistency S Chib, TA Kuffner arXiv preprint arXiv:1607.00292, 2016 | 35 | 2016 |
| On overfitting and post-selection uncertainty assessments L Hong, TA Kuffner, R Martin Biometrika 105 (1), 221-224, 2018 | 31 | 2018 |
| Modeling autosomal dominant Alzheimer's disease with machine learning PH Luckett, A McCullough, BA Gordon, J Strain, S Flores, A Dincer, ... Alzheimer's & Dementia 17 (6), 1005-1016, 2021 | 18 | 2021 |
| On prediction of future insurance claims when the model is uncertain L Hong, T Kuffner, R Martin Variance 12 (1), 2019 | 14 | 2019 |
| On model selection criteria for climate change impact studies X Cui, B Gafarov, D Ghanem, T Kuffner Journal of Econometrics 239 (1), 105511, 2024 | 9 | 2024 |
| Principled statistical inference in data science TA Kuffner, GA Young Statistical Data Science, 21-36, 2018 | 8 | 2018 |
| On the validity of the formal Edgeworth expansion for posterior densities JE Kolassa, TA Kuffner | 7 | 2020 |
| Stability and uniqueness of p-values for likelihood-based inference TJ DiCiccio, TA Kuffner, GA Young, R Zaretzki Statistica Sinica, 1355-1376, 2015 | 7 | 2015 |
| A simple analysis of the exact probability matching prior in the location-scale model TJ DiCiccio, TA Kuffner, GA Young The American Statistician 71 (4), 302-304, 2017 | 5 | 2017 |
| Online bootstrap inference with nonconvex stochastic gradient descent estimator Y Zhong, T Kuffner, S Lahiri arXiv preprint arXiv:2306.02205, 2023 | 4 | 2023 |
| Consistency of a hybrid block bootstrap for distribution and variance estimation for sample quantiles of weakly dependent sequences TA Kuffner, SMS Lee, GA Young Australian & New Zealand Journal of Statistics 60 (1), 103-114, 2018 | 4 | 2018 |
| On model selection criteria for climate change impact studies X Cui, B Gafarov, D Ghanem, T Kuffner arXiv preprint arXiv:1808.07861, 2018 | 3 | 2018 |
| Quantifying nuisance parameter effects via decompositions of asymptotic refinements for likelihood-based statistics TJ DiCiccio, TA Kuffner, GA Young Journal of Statistical Planning and Inference 165, 1-12, 2015 | 3 | 2015 |
| Conditional Randomization Rank Test Y Zhong, T Kuffner, S Lahiri arXiv preprint arXiv:2112.00258, 2021 | 2 | 2021 |
| Bayesian inference on volatility in the presence of infinite jump activity and microstructure noise Q Wang, JE Figueroa-López, TA Kuffner | 2 | 2021 |
| Block bootstrap optimality and empirical block selection for sample quantiles with dependent data TA Kuffner, SMS Lee, GA Young Biometrika 108 (3), 675-692, 2021 | 1 | 2021 |
| Optimal hybrid block bootstrap for sample quantiles under weak dependence TA Kuffner, S Lee, GA Young arXiv preprint arXiv:1710.02537, 2017 | 1 | 2017 |
| Objective Bayes, conditional inference and the signed root likelihood ratio statistic TJ Diciccio, TA Kuffner, GA Young Biometrika 99 (3), 675-686, 2012 | 1 | 2012 |
Alastair YoungProfessor of Statistics在 imperial.ac.uk 的电子邮件经过验证
