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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
Data Harmonization Via Regularized Nonparametric Mixing Distribution Estimation Steven Wilkins-Reeves, Yen-Chi Chen, and Kwun Chuen (Gary) Chan
Assessing Influential Observations in Pain Prediction using fMRI Data Dongliang Zhang, Masoud Asgharian, and Martin A. Lindquist
B-BIND: Biophysical Bayesian Inference for Neurodegenerative Dynamics Anamika Agrawal, Victoria M. Rachleff, Kyle J. Travaglini, Shubhabrata Mukherjee, Paul K. Crane, Michael Hawrylycz, Dirk C. Keene, Ed Lein, Gonzalo Mena, and Mariano Ignacio Gabitto
A Bayesian Reinforcement Learning Framework for Optimizing the BCI-utility of P300 Brain-Computer Interfaces Bangyao Zhao, Yixin Wang, Jane Huggins, and Jian Kang
A Bayesian Joint Model of Multiple Longitudinal and Categorical Outcomes with Application to Multiple Myeloma Using Permutation-Based Variable Importance Danilo Alvares
Temporal Models for Estimation and Short-Term Forecasting of Neonatal Mortality Rates in Sub-Saharan Africa Katherine R Paulson, Geir-Arne Fuglstad, Zehang Richard Li, and Jonathan Wakefield
Analysing Dynamic Cross-Price Dependencies with a Markov-Switching Spatial Autoregressive Model Matteo Iacopini, Tamas Krisztin, and Philipp Piribauer
Bayesian Image-on-Image Regression via Deep Kernel Learning based Gaussian Processes Guoxuan Ma, Bangyao Zhao, Hasan Abu-Amara and Jian Kang
Moving Towards Automated Interstellar Boundary Explorer Data Selection with LOTUS Madeline A. Stricklin, Lauren J. Beesley, Brian P. Weaver, Kelly R. Moran, Dave Osthus, Paul H. Janzen, Grant David Meadors and Daniel B. Reisenfeld
Functional Mixture Regression Control Chart Christian Capezza, Fabio Centofanti, Davide Forcina, Antonio Lepore and Biagio Palumbo
Latent Class Analysis with Discrete Failure Time Model Qinmengge Li, Kevin He, Lam C. Tsoi and Jian Kang
Statistical Inference for Covariate-Adjusted and Interpretable Generalized Latent Factor Model with Application to Testing Fairness Jing Ouyang, Chengyu Cui, Kean Ming Tan and Gongjun Xu
k-Contact Distance for Noisy Nonhomogeneous Spatial Point Data with application to Repeating Fast Radio Burst sources from CHIME/FRB A. M. Cook, Dayi Li, Gwendolyn M. Eadie, David C. Stenning, Paul Scholz, Derek Bingham, Radu Craiu, B. M. Gaensler, Kiyoshi W. Masui, Ziggy Pleunis, Antonio Herrera-Martin, Ronniy C. Joseph, Ayush Pandhi, Aaron B. Pearlman and J. Xavier Prochaska
Integrative Learning of Linear Non-Gaussian Directed Acyclic Graphs with Application on Multi-Source Gene Regulatory Network Analysis Xuanyu Li, Sanguo Zhang, Mingyang Ren and Qingzhao Zhang
Multiply robust estimation for causal survival analysis with treatment noncompliance Chao Cheng, Bo Liu, Lisa Wruck, Fan Li and Fan Li
Inferring the effect of a randomised treatment on a recurrent event process under dependent censoring Wout Waterschoot, Andrea Callegaro, Luca Moraschini and Stijn Vansteelandt
Identification of Genetic Factors Associated with Corpus Callosum Morphology: Conditional Strong Independence Screening for Non-Euclidean Responses Zhe Gao, Jin Zhu, Yue Hu, Wenliang Pan and Xueqin Wang
Spatio-Temporal-Network Point Processes for Modeling Crime Events with Landmarks Zheng Dong, Jorge Mateu and Yao Xie
Latent Space Modeling for Human Disease Network with Temporal Variations: Analysis of Medicare Data Guojun Zhu, Ruiyue Wang, Rong Li, Sanguo Zhang, Shuangge Ma, Guanzhong Qiao and Hao Mei
Quantiled conditional variance, skewness, and kurtosis by Cornish-Fisher expansion Ningning Zhang and Ke Zhu
Ranking and Selection in Large- Scale Inference of Heteroscedastic Units Wenguang Sun
Neural Posterior Estimation with Autoregressive Tiling for Detecting Objects in Astronomical Images Jeffrey Regier
Random forests and mixed effects random forests for small area estimation of general parameters: A poverty mapping case study in Mozambique Patrick Krennmair, Nora Würz, Timo Schmid and Nikos Tzavidis
Feature Augmentations for High-Dimensional Learning: Applications to Stock Market Prediction Using Chinese News Data Xiaonan Zhu, Bingyan Wang and Jianqing Fan
A Data Envelopment Analysis Approach for Assessing Fairness in Resource Allocation: Application to Kidney Exchange Programs Ali Kaazempur-Mofrad and Xiaowu Dai