Heavy-tailed $p$-value combinations from the perspective of extreme value theory
Fuente:
arXiv
Saved in:
| Main Author: | Rho, Yeonwoo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Locally tail-scale invariant scoring rules for evaluation of extreme value forecasts
by: Olafsdottir, Helga Kristin, et al.
Published: (2023)
by: Olafsdottir, Helga Kristin, et al.
Published: (2023)
Censored extreme value estimation
by: Bladt, Martin, et al.
Published: (2023)
by: Bladt, Martin, et al.
Published: (2023)
Trends in tail dependence of heteroscedastic extremes
by: Einmahl, John H. J., et al.
Published: (2026)
by: Einmahl, John H. J., et al.
Published: (2026)
Introducing the b-value: combining unbiased and biased estimators from a sensitivity analysis perspective
by: Lin, Zhexiao, et al.
Published: (2026)
by: Lin, Zhexiao, et al.
Published: (2026)
E-values as statistical evidence: A comparison to Bayes factors, likelihoods, and p-values
by: Chugg, Ben, et al.
Published: (2026)
by: Chugg, Ben, et al.
Published: (2026)
Selective inference is easier with p-values
by: Sood, Anav
Published: (2024)
by: Sood, Anav
Published: (2024)
On the existence of powerful p-values and e-values for composite hypotheses
by: Zhang, Zhenyuan, et al.
Published: (2023)
by: Zhang, Zhenyuan, et al.
Published: (2023)
False discovery rate control with compound p-values
by: Barber, Rina Foygel, et al.
Published: (2025)
by: Barber, Rina Foygel, et al.
Published: (2025)
Censored and extreme losses: functional convergence and applications to tail goodness-of-fit
by: Bladt, Martin, et al.
Published: (2024)
by: Bladt, Martin, et al.
Published: (2024)
Variance-reduced extreme value index estimators using control variates in a semi-supervised setting
by: Bocquet-Nouaille, Louison, et al.
Published: (2025)
by: Bocquet-Nouaille, Louison, et al.
Published: (2025)
Post-hoc $α$ Hypothesis Testing and the Post-hoc $p$-value
by: Koning, Nick W.
Published: (2023)
by: Koning, Nick W.
Published: (2023)
Asymptotically well-calibrated Bayesian $p$-value using the Kolmogorov-Smirnov statistic
by: Shen, Yueming, et al.
Published: (2025)
by: Shen, Yueming, et al.
Published: (2025)
Rank-transformed subsampling: inference for multiple data splitting and exchangeable p-values
by: Guo, F. Richard, et al.
Published: (2023)
by: Guo, F. Richard, et al.
Published: (2023)
Testing for Outliers with Conformal p-values
by: Bates, Stephen, et al.
Published: (2021)
by: Bates, Stephen, et al.
Published: (2021)
On the universal calibration of heavy-tailed combination tests
by: Chakraborty, Parijat, et al.
Published: (2025)
by: Chakraborty, Parijat, et al.
Published: (2025)
Hypothesis testing with e-values
by: Ramdas, Aaditya, et al.
Published: (2024)
by: Ramdas, Aaditya, et al.
Published: (2024)
Robust Inference for High-dimensional Linear Models with Heavy-tailed Errors via Partial Gini Covariance
by: Zhang, Yilin, et al.
Published: (2024)
by: Zhang, Yilin, et al.
Published: (2024)
Mixture Matrix-valued Autoregressive Model
by: Wu, Fei, et al.
Published: (2023)
by: Wu, Fei, et al.
Published: (2023)
Controlling the false discovery rate in high-dimensional linear models using model-X knockoffs and $p$-values
by: Chang, Jinyuan, et al.
Published: (2025)
by: Chang, Jinyuan, et al.
Published: (2025)
Direct Bayesian Regression for Distribution-valued Covariates
by: Tang, Bohao, et al.
Published: (2023)
by: Tang, Bohao, et al.
Published: (2023)
Theoretical guarantees for change localization using conformal p-values
by: Bhattacharyya, Swapnaneel, et al.
Published: (2025)
by: Bhattacharyya, Swapnaneel, et al.
Published: (2025)
E-values for k-Sample Tests With Exponential Families
by: Hao, Yunda, et al.
Published: (2023)
by: Hao, Yunda, et al.
Published: (2023)
Change-Point Detection for Object-valued Time Series
by: Zhang, Yi, et al.
Published: (2026)
by: Zhang, Yi, et al.
Published: (2026)
Offline changepoint localization using a matrix of conformal p-values
by: Dandapanthula, Sanjit, et al.
Published: (2025)
by: Dandapanthula, Sanjit, et al.
Published: (2025)
Measuring Evidence against Exchangeability and Group Invariance with E-values
by: Koning, Nick W.
Published: (2023)
by: Koning, Nick W.
Published: (2023)
Post-selection inference for e-value based confidence intervals
by: Xu, Ziyu, et al.
Published: (2022)
by: Xu, Ziyu, et al.
Published: (2022)
IV regression with distribution-valued outcomes
by: Van Dijcke, David, et al.
Published: (2026)
by: Van Dijcke, David, et al.
Published: (2026)
Exact P-values for Network Interference
by: Athey, Susan, et al.
Published: (2015)
by: Athey, Susan, et al.
Published: (2015)
Dempster-Shafer P-values: Thoughts on an Alternative Approach for Multinomial Inference
by: Hoffman, Kentaro, et al.
Published: (2024)
by: Hoffman, Kentaro, et al.
Published: (2024)
Set-valued data analysis for interlaboratory comparisons
by: Petit, Sébastien, et al.
Published: (2025)
by: Petit, Sébastien, et al.
Published: (2025)
Tiny but uniform improvements of adaptive BH procedures via compound e-values
by: Ignatiadis, Nikolaos, et al.
Published: (2026)
by: Ignatiadis, Nikolaos, et al.
Published: (2026)
A Kullback-Leibler divergence test for multivariate extremes: theory and practice
by: Engelke, Sebastian, et al.
Published: (2026)
by: Engelke, Sebastian, et al.
Published: (2026)
Generalized projection tests for function-valued parameters with applications to testing structural causal assumptions
by: Wang, Rui, et al.
Published: (2026)
by: Wang, Rui, et al.
Published: (2026)
A General Framework for Multiple Testing via E-value Aggregation and Data-Dependent Weighting
by: Li, Guanxun, et al.
Published: (2023)
by: Li, Guanxun, et al.
Published: (2023)
Improving online FDR procedures via online analogs of e-closure and compound e-values
by: Xu, Ziyu, et al.
Published: (2026)
by: Xu, Ziyu, et al.
Published: (2026)
Modelling multivariate extreme value distributions via Markov trees
by: Hu, Shuang, et al.
Published: (2022)
by: Hu, Shuang, et al.
Published: (2022)
Deep neural expected shortfall regression with tail-robustness
by: Yu, Myeonghun, et al.
Published: (2025)
by: Yu, Myeonghun, et al.
Published: (2025)
Heavy-tailed Contamination is Easier than Adversarial Contamination
by: Cherapanamjeri, Yeshwanth, et al.
Published: (2024)
by: Cherapanamjeri, Yeshwanth, et al.
Published: (2024)
The $s$-value: evaluating stability with respect to distributional shifts
by: Gupta, Suyash, et al.
Published: (2021)
by: Gupta, Suyash, et al.
Published: (2021)
Spatial modeling of extremes and an angular component
by: Tamagny, Gaspard, et al.
Published: (2023)
by: Tamagny, Gaspard, et al.
Published: (2023)
Similar Items
-
Locally tail-scale invariant scoring rules for evaluation of extreme value forecasts
by: Olafsdottir, Helga Kristin, et al.
Published: (2023) -
Censored extreme value estimation
by: Bladt, Martin, et al.
Published: (2023) -
Trends in tail dependence of heteroscedastic extremes
by: Einmahl, John H. J., et al.
Published: (2026) -
Introducing the b-value: combining unbiased and biased estimators from a sensitivity analysis perspective
by: Lin, Zhexiao, et al.
Published: (2026) -
E-values as statistical evidence: A comparison to Bayes factors, likelihoods, and p-values
by: Chugg, Ben, et al.
Published: (2026)