Papers to Appear in Subsequent Issues

When papers are accepted for publication, they will appear below. Any changes that are made during the production process will only appear in the final version. Papers listed here are not updated during the production process and are removed once an issue is published.

Testing network correlation efficiently via counting trees Cheng Mao, Yihong Wu, Jiaming Xu, and Sophie H. Yu
Statistical inference for rough volatility: Minimax Theory Carsten Chong, Marc Hoffmann, Yanghui Liu, Mathieu Rosenbaum, and Gregoire Szymanski
High-Dimensional Inference for Dynamic Treatment Effects Jelena Bradic, Weijie Ji, and Yuqian Zhang
The curse of overparametrization in adversarial training: Precise analysis of robust generalization for random features regression Adel Javanmard and Hamed Hassani
Convergence Rates of Oblique Regression Trees for Flexible Function Libraries Matias Damian Cattaneo, Rajita Chandak, and Jason Matthew Klusowski
Early stopping for L2-boosting in high-dimensional linear models Bernhard Stankewitz
Inference for diffusions from low frequency measurements Richard Nickl
A general framework to quantify deviations from structural assumptions in the analysis of  nonstationary function-valued processes Anne Margrete Nicolien van Delft and Holger Dette
The edge of discovery: Controlling the local false discovery rate at the margin Jake A Soloff, Daniel Xiang, and William Fithian
2 Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM Jiaqi L, Likai Chen, Weining Wang, and Wei Biao Wu
Testing for practically significant  dependencies in high dimensions via bootstrapping maxima of U-statistics Patrick Bastian, Holger Dette, and Johannes Heiny
Transfer Learning for Functional Mean Estimation: Phase Transition and Adaptive Algorithms Tony Cai, Dongwoo Kim, and Hongming Pu
Finding Optimal Dynamic Treatment Regimes Using Smooth Fisher Consistent Surrogate Loss Nilanjana Laha
Optimal parameter estimation for linear SPDEs from multiple measurements Randolf Altmeyer, Anton Tiepner, and Martin Wahl
Edge Differentially Private Estimation in the β-model via Jittering and Method of Moments Jinyuan Chang, Qiao Hu, Eric Kolaczyk, Qiwei Yao, and Fengting Yi
Inference for Heteroskedastic PCA with Missing Data Yuling Yan, Yuxin Chen, and Jianqing Fan
Dimension-Free Mixing Times of Gibbs Samplers for Bayesian Hierarchical Models Filippo Ascolani and Giacomo Zanella
Metric Statistics: Exploration and Inference for Random Objects With Distance Profiles Paromita Dubey, Yaqing Chen, and Hans-Georg Müller
Minimax rates for heterogeneous causal effect estimation Edward H Kennedy, Sivaraman Balakrishnan, James M Robins, and Larry Wasserman
The Online Closure Principle Lasse Fischer, Marta Bofill Roig, and Werner Brannath
Parameter Estimation in Nonlinear Multivariate Stochastic Differential Equations Based on Splitting Schemes Predrag Pilipovic, Adeline Samson, and Susanne Ditlevsen
Reconciling model-X and doubly robust approaches to conditional independence testing Ziang Niu, Abhinav Chakraborty, Oliver Dukes, and Eugene Katsevich
Non-independent component analysis Geert Mesters and Piotr Zwiernik