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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.

Boosting Data Analytics with Synthetic Volume Expansion Xiaotong Shen, Yifei Liu, and Rex Shen
HEDE: Heritability Estimation in High Dimensions by Ensembling Debiased Estimators in Genome-Wide Association Studies Yanke Song, Xihong Lin and Pragya Sur
Estimation of total mediation effect for a binary trait in a case-control study for high-dimensional omics mediators Zhiyu Kang, Li Chen, Peng Wei, Zhichao Xu, Chunlin Li and Tianzhong Yang
Spatially Randomized Designs Can Enhance Policy Evaluation Ying Yang, Chengchun Shi, Fang Yao, Shouyang Wang and Hongtu Zhu
Spatial causal inference in the presence of unmeasured confounding and interference Georgia Papadogeorgou and Srijata Samanta
A Topological Gaussian Mixture Model for Bone Marrow Morphology in Leukaemia Qiquan Wang, Anna Song, Antoniana Batsivari, Dominique Bonnet and Anthea Monod
Joint Modeling of Spatial Dependencies Across Multiple Subjects in Multiplexed Tissue Imaging Joel Eliason, Arvind Rao, Timothy Frankel and Michele Peruzzi
Adaptive Frequency Band Learning of Nonstationary Functional Time Series: An Application to High-Dimensional EEG Signals Pramita Bagchi and Scott Alan Bruce
A scalable path algorithm for clusterwise messaging component analysis in digital communications Rashmi Ranjan Bhuyian, Wreetabrata Kar and Gourab Mukherjee
Spatial causal inference in the presence of preferential sampling to study the impacts of marine protected areas Dongjae Son, Brian J. Reich, Erin M. Schliep, Shu Yang and David A. Gill
Detecting Breast Carcinoma Metastasis on Whole-Slide Images by Partially Subsampled Multiple Instance Learning Baichen Yu, Xuetong Li, Jing Zhou and Hansheng Wang
Deep Learning of Semi-Competing Risk Data via a New Neural Expectation-Maximization Algorithm Stephen Salerno, Zhilin Zhang and Yi Li
Penalized FCI for Causal Structure Learning in a Sparse DAG for Biomarker Discovery in Parkinson’s Disease Samhita Pal, Dhrubajyoti Ghosh and Shu Yang
Addressing Phase Discrepancies in Functional Data: A Bayesian Approach for Accurate Alignment and Smoothing Jacopo Gardella, Raffaele Argiento, Alessandro Casa and Alessia Pini
Raking mortality rates across cause, population group and geography with variance estimation Ariane Ducellier, Alexander Hsu, Parkes Kendrick, Bill Gustavson, Laura Dwyer-Lindgren, Christopher Murray, Peng Zheng and Aleksandr Aravkin
Multilevel Primary Aim Analyses of Clustered SMARTs: With Applications in Health Policy Gabriel Durham, Anil Battalahalli, Amy Kilbourne, Andrew Quanbeck, Wenchu Pan, Tim Lycurgus and Daniel Almirall
Longitudinal Causal Inference with Selective Eligibility: Application to Pretrial Risk Assessment Zhichao Jiang, Eli Ben-Michael, D. James Greiner, Ryan Halen and Kosuke Imai
A Bayesian hierarchical model for methane emission source apportionment William S. Daniels, Douglas W. Nychka and Dorit M. Hammerling
BayesFLo: Bayesian fault localization of complex software systems Yi Ji, Simon Mak, Ryan Lekivetz and Joseph Morgan
Statistical Opportunities in Neuroimaging Hongtu Zhu
Privacy-Protected Spatial Autoregressive Models with Applications Danyang Huang, Ziyi Kong, Shuyuan Wu and Hansheng Wang
Signal Lasso with Non-Convex Penalties for Efficient Network Reconstruction in Complex System Lei Shi, Jie Hu, Libin Jin, Huaiyu Tan, Wei Zhong and Chen Shen
Modeling and prediction of mutation fitness on protein functionality with structural information using high-dimensional Potts model Wen Zhou, Bingying Dai, Yinan Lin, Zhao Ren and Kejue Jia
A case-control sampling strategy for zero-inflated models with an application to female sex worker mapping in sub-Saharan Africa Sanam Sanei, Ian Laga, Sharon Weir and Le Bao
Neuron Dynamic Modeling with Random Trial Effects Hongyang Lu, Yunpeng Zhao, Dong Song and Haonan Wang
Bayesian Empirical Likelihood for Ultra-High Dimensional Variable Selection With Application to Drug Sensitivity Can Xu, Zeyu Lu, Yichen Cheng, Qifan Song, Yichuan Zhao and Xinlei Wang
Efficient Surgical Tool Recognition via HMM-Stabilized Deep Learning Haifeng Wang, Hao Xu, Jun Wang, Jian Zhou and Deng Ke
Semi-supervised Estimation of Survival Rate with Doubly-censored Survival Data Yang Wang, Qingning Zhou, Tianxi Cai and Xuan Wang
Quantifying uncertainty in climate projections with conformal ensembles Trevor Harris and Ryan Sriver
Federated Ensemble Clustering for Integrative Analysis of Multi-Source Data Xin Xiong, Jueyi Liu, Katherine P. Liao, Tianxi Cai and Rui Duan
PPI++: Efficient Prediction-Powered Inference Anastasios N. Angelopoulos, John C. Duchi and Tijana Zrnic
Estimating Time-Varying Epidemic Severity Rates with Adaptive Deconvolution Jeremy Goldwasser, Addison J. Hu, Alyssa Bilinski, Daniel J. McDonald and Ryan J. Tibshirani
Bayesian Modeling of TVP-VARs Using Regression Trees Niko Hauzenberger, Florian Huber, Gary Koop and James Mitchell
A joint model of the individual mean and within-subject variability of a longitudinal outcome with a competing risks time-to-event outcome Shanpeng Li, Daniel S. Nuyujukian, Robyn L. McClelland, Peter D. Reaven, Jin Zhou, Hua Zhou and Gang Li
A Generalized Phase 1-2-3 Design for Optimizing Doses and Comparing Treatments Within Subgroups Saijun Zhao, Yong Zang and Peter F. Thall
A Counterfactual Framework for Estimating Infectious Disease Prevalence under Repeated Testing with Symptomatic and Contact-Tracing Components Jeongjin Lee, Junke Yang, Grzegorz Rempala and Patrick Schnell
SADA: Safe and Adaptive Aggregation of Multiple Black-Box Predictions in Semi-Supervised Learning Jiawei Shan, Zhifeng Chen, Yiming Dong, Yazhen Wang and Jiwei Zhao
A Generalized Additive Partial-Mastery Cognitive Diagnosis Model Camilo Cárdenas Hurtado, Sze Ming Lee, Yunxiao Chen and Irini Moustaki
Integrated Weighted Association Test with Application to Genetic Association Studies Hong Zhang, Ming Liu, John E Landers and Zheyang Wu
Nested Atoms Model with Application to Clustering Big Population-Scale Single-Cell Data Arhit Chakrabarti, Yang Ni, Yuchao Jiang and Bani K. Mallick
Bayesian Probit Multi-Study Non-negative Matrix Factorization for Mutational Signatures Blake Hansen, Isabella Grabski, Giovanni Parmigiani and Roberta De Vito
CNV-profile regression for copy number variant association analysis with whole genome sequencing data Yaqin Si, Wenbin Lu, Shannon T. Holloway, Hui Wang, Albert A. Tucci, Yuhuan Cheng, Amanda Brucker, Gerard D. Schellenberg, Li-San Wang, Wan-Ping Lee and Jung-Ying Tzeng
Goodness of Fit for Bayesian Generative Models with Applications in Population Genetics Jean-Michel Marin, Arnaud Estoup, Paul Bastide and Guillaume Le Mailloux
Classifying Metamorphic versus Single-Fold Proteins with Statistical Learning and AlphaFold2 Yongkai Chen, Samuel Wong and Samuel Kou
Primal–Dual Alternating Neural Learning for Timely Classification with Performance Guarantees Jiaming Qiu, Yingye Zheng and Ying-Qi Zhao
Scale Reliant Inference Michelle Pistner Nixon, Kyle C McGovern, Maxwell A Konnaris, Jeffrey Letourneau, Lawrence A David, Nicole A Lazar, Sayan Mukherjee and Justin D Silverman
Robust Spatiotemporal Epidemic Modeling with Integrated Adaptive Outlier Detection Haoming Shi, Shan Yu and Eric C. Chi
A functional landmark flexible-hazards cure model for individual dynamic prediction Can Xie, Ruosha Li, Jeffrey Morris, Nicholas Short, Hagop Kantarjian and Xuelin Huang