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ORCIDJournal of Computational and Graphical Statistics, Volume 32
Volume 32, Number 1, January 2023
- Correction. i
- Flávio B. Gonçalves
, Bárbara C. C. Dias:
Exact Bayesian Inference for Level-Set Cox Processes with Piecewise Constant Intensity Function. 1-18 - Agnieszka Borowska, Ruth King:
Semi-Complete Data Augmentation for Efficient State Space Model Fitting. 19-35 - Chris Sherlock, Andrew Golightly:
Exact Bayesian Inference for Discretely Observed Markov Jump Processes Using Finite Rate Matrices. 36-48 - Fan Yin, Guanyu Hu, Weining Shen:
Analysis of Professional Basketball Field Goal Attempts via a Bayesian Matrix Clustering Approach. 49-60 - Dongjin Li, Somak Dutta, Vivekananda Roy:
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings. 61-73 - Sarah E. Heaps:
Enforcing Stationarity through the Prior in Vector Autoregressions. 74-83 - Alex Stringer, Patrick E. Brown, Jamie Stafford:
Fast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models. 84-98 - Marianne Menictas, Gioia Di Credico, Matt P. Wand:
Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects. 99-115 - Francesco Sanna Passino, Nicholas A. Heard:
Mutually Exciting Point Process Graphs for Modeling Dynamic Networks. 116-130 - John Koo, Minh Tang, Michael W. Trosset:
Popularity Adjusted Block Models are Generalized Random Dot Product Graphs. 131-144 - Avanti Athreya, Zachary Lubberts, Carey E. Priebe, Youngser Park, Minh Tang, Vince Lyzinski, Michael J. Kane, Bryan W. Lewis:
Numerical Tolerance for Spectral Decompositions of Random Matrices and Applications to Network Inference. 145-156 - Aramayis Dallakyan, Mohsen Pourahmadi:
Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Replicated Time Series. 157-170 - Barinder Thind, Kevin Multani, Jiguo Cao:
Deep Learning With Functional Inputs. 171-180 - Shih-Ting Huang, Johannes Lederer:
DeepMoM: Robust Deep Learning With Median-of-Means. 181-195 - David Degras:
Scalable Feature Matching Across Large Data Collections. 196-212 - Florian Hébert, David Causeur, Mathieu Emily:
Adaptive Handling of Dependence in High-Dimensional Regression Modeling. 213-225 - Zhenyu Wei, Thomas C. M. Lee:
High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference. 226-240 - Xinmin Li, Feifei Chen, Hua Liang, David Ruppert:
Model Checking for Logistic Models When the Number of Parameters Tends to Infinity. 241-251 - Jingfei Zhang, Will Wei Sun, Lexin Li:
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies. 252-262 - Jialu Li, Guan Yu, Qizhai Li, Yufeng Liu:
Sample-Wise Combined Missing Effect Model with Penalization. 263-274 - Jingwei Liang, Clarice Poon:
Variable Screening for Sparse Online Regression. 275-293 - Adam B. Kashlak, Sergii Myroshnychenko, Susanna Spektor:
Analytic Permutation Testing for Functional Data ANOVA. 294-303 - Jicai Liu, Jinhong Li, Riquan Zhang:
K-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function. 304-318 - Matthys Lucas Steyn, Tertius de Wet, Bernard De Baets, Stijn Luca:
A Nearest Neighbor Open-Set Classifier based on Excesses of Distance Ratios. 319-328 - Jingyi Zhang, Cheng Meng, Jun Yu, Mengrui Zhang, Wenxuan Zhong, Ping Ma:
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation. 329-339
Volume 32, Number 2, April 2023
- Antonio Elías, Raúl Jiménez, Anna Maria Paganoni, Laura M. Sangalli:
Integrated Depths for Partially Observed Functional Data. 341-352 - Shuning Huo, Jeffrey S. Morris, Hongxiao Zhu:
Ultra-Fast Approximate Inference Using Variational Functional Mixed Models. 353-365 - Erjia Cui, Ruonan Li, Ciprian M. Crainiceanu, Luo Xiao:
Fast Multilevel Functional Principal Component Analysis. 366-377 - Eugen Pircalabelu, Gerda Claeskens:
Linear Manifold Modeling and Graph Estimation based on Multivariate Functional Data with Different Coarseness Scales. 378-387 - Bart Blackburn, Mark S. Handcock:
Practical Network Modeling via Tapered Exponential-Family Random Graph Models. 388-401 - Kai Kang, Xinyuan Song:
Joint Modeling of Longitudinal Imaging and Survival Data. 402-412 - Amanda F. Mejia, David Bolin, Yu Ryan Yue, Jiongran Wang, Brian S. Caffo, Mary Beth Nebel:
Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference. 413-433 - Jiaqi Gu, Guosheng Yin:
Triangular Concordance Learning of Networks. 434-447 - Tianning Dong, Peiyi Zhang, Faming Liang:
A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters. 448-469 - Ruoshui Zhai, Roee Gutman:
A Bayesian Singular Value Decomposition Procedure for Missing Data Imputation. 470-482 - Luiza S. C. Piancastelli, Nial Friel, Wagner Barreto-Souza, Hernando C. Ombao:
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference. 483-500 - Vivekananda Roy, Lijin Zhang:
Convergence of Position-Dependent MALA with Application to Conditional Simulation in GLMMs. 501-512 - Miguel Biron-Lattes, Alexandre Bouchard-Côté, Trevor Campbell:
Pseudo-Marginal Inference for CTMCs on Infinite Spaces via Monotonic Likelihood Approximations. 513-527 - Kan Chen, Siyu Heng, Qi Long, Bo Zhang:
Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies. 528-538 - Johannes Resin:
A Simple Algorithm for Exact Multinomial Tests. 539-550 - Etor Arza, Josu Ceberio, Ekhiñe Irurozki, Aritz Pérez:
Comparing Two Samples Through Stochastic Dominance: A Graphical Approach. 551-566 - Michael C. Sachs, Gustav Jonzon, Arvid Sjölander, Erin E. Gabriel:
A General Method for Deriving Tight Symbolic Bounds on Causal Effects. 567-576 - Yiqun Chen, Sean Jewell, Daniela M. Witten:
More Powerful Selective Inference for the Graph Fused Lasso. 577-587 - Weichang Yu, Sara Wade, Howard D. Bondell, Lamiae Azizi:
Nonstationary Gaussian Process Discriminant Analysis With Variable Selection for High-Dimensional Functional Data. 588-600 - Philippe Boileau, Nima S. Hejazi, Mark J. van der Laan, Sandrine Dudoit:
Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions. 601-612 - Ming-Chung Chang:
Predictive Subdata Selection for Computer Models. 613-630 - Daniel Schalk, Bernd Bischl, David Rügamer:
Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization. 631-641 - Honghe Jin, Lynne Billard:
Copulas and Histogram-Valued Data. 642-657 - Mohsen Taheri, Jörn Schulz:
Statistical Analysis of Locally Parameterized Shapes. 658-670 - Tullia Padellini, Pierpaolo Brutti:
Persistence Flamelets: Topological Invariants for Scale Spaces. 671-683 - Anastasia Ushakova, Simon A. Taylor, Rebecca Killick:
Micro-Macro Changepoint Inference for Periodic Data Sequences. 684-695 - Philipp Otto, Rick Steinert:
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks. 696-711 - Charles A. Pehlivanian, Daniel B. Neill:
Efficient Optimization of Partition Scan Statistics via the Consecutive Partitions Property. 712-729 - Bin Guo, Lynn E. Eberly, Pierre-Gilles Henry, Christophe Lenglet, Eric F. Lock:
Multiway Sparse Distance Weighted Discrimination. 730-743 - Weng Kee Wong, Julie Zhou:
Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives. 744-753 - Lucy D'Agostino McGowan, Roger D. Peng, Stephanie C. Hicks:
Design Principles for Data Analysis. 754-761
Volume 32, Number 3, 2023
- Bradley S. Price, John P. Saldanha, Dariane Drake, Katherine Kopp:
Lessons from West Virginia's Pandemic Response. 763-764 - Cornelius Fritz, Giacomo De Nicola, Felix Günther, David Rügamer, Martje Rave, Marc Schneble, Andreas Bender, Maximilian Weigert, Ralph Brinks, Annika Hoyer, Ursula Berger, Helmut Küchenhoff, Göran Kauermann:
Challenges in Interpreting Epidemiological Surveillance Data - Experiences from Germany. 765-766 - Emanuele Borgonovo, Xuefei Lu, Giovanni Rabitti:
Sensitivity Analysis of Pandemic Models Can Support Effective Policy Decisions. 767-768 - Michael Stanley Smith, Ruben Loaiza-Maya:
Implicit Copula Variational Inference. 769-781 - Chong You, John T. Ormerod, Xiangyang Li, Cheng Heng Pang, Xiao-Hua Zhou:
An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression. 782-792 - David T. Frazier, Ruben Loaiza-Maya, Gael M. Martin:
Variational Bayes in State Space Models: Inferential and Predictive Accuracy. 793-804 - Joaquín Martínez-Minaya, Finn Lindgren, Antonio López-Quílez, Daniel Simpson, David V. Conesa:
The Integrated Nested Laplace Approximation for Fitting Dirichlet Regression Models. 805-823 - Annie Sauer, Andrew Cooper, Robert B. Gramacy:
Vecchia-Approximated Deep Gaussian Processes for Computer Experiments. 824-837 - Chencheng Cai, Rong Chen, Han Xiao:
Hybrid Kronecker Product Decomposition and Approximation. 838-852 - Xin Xiong, Ivor Cribben:
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model. 853-872 - Xiao Zhang, Xingjie Shi, Yiming Liu, Xu Liu, Shuangge Ma:
A General Framework for Identifying Hierarchical Interactions and Its Application to Genomics Data. 873-883 - Canyi Chen, Liping Zhu:
Distributed Decoding From Heterogeneous 1-Bit Compressive Measurements. 884-894 - Jiayuan Zhou, Kshitij Khare, Sanvesh Srivastava:
Asynchronous and Distributed Data Augmentation for Massive Data Settings. 895-907 - Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa:
On Data Augmentation for Models Involving Reciprocal Gamma Functions. 908-916 - Laura D'angelo, Antonio Canale:
Efficient Posterior Sampling for Bayesian Poisson Regression. 917-926 - Siyu Yi, Ze Liu, Min-Qian Liu, Yong-Dao Zhou:
Global Likelihood Sampler for Multimodal Distributions. 927-937 - Qiang Heng, Hua Zhou, Eric C. Chi:
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo. 938-949 - Mirrelijn M. van Nee, Tim van de Brug, Mark A. van de Wiel:
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net. 950-960 - Le Chang, Alan H. Welsh:
Robust Multivariate Lasso Regression with Covariance Estimation. 961-973 - Canhong Wen, Qin Wang, Yuan Jiang:
Stability Approach to Regularization Selection for Reduced-Rank Regression. 974-984 - Mauro Bernardi, Antonio Canale, Marco Stefanucci:
Locally Sparse Function-on-Function Regression. 985-999 - Peijun Sang, Adam B. Kashlak, Linglong Kong:
A Reproducing Kernel Hilbert Space Framework for Functional Classification. 1000-1008 - Cunjie Lin, Jingfu Peng, Yichen Qin, Yang Li, Yuhong Yang:
Optimal Integrating Learning for Split Questionnaire Design Type Data. 1009-1023 - Pavlos Zoubouloglou, Eduardo García-Portugués, J. S. Marron:
Scaled Torus Principal Component Analysis. 1024-1035 - Lili Wu, Shu Yang:
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data. 1036-1045 - Antonio R. Linero, Junliang Du:
Gibbs Priors for Bayesian Nonparametric Variable Selection with Weak Learners. 1046-1059 - Gunwoong Park:
Computationally Efficient Learning of Gaussian Linear Structural Equation Models with Equal Error Variances. 1060-1073 - Changcheng Li, Runze Li, Jiawei Wen, Songshan Yang, Xiang Zhan:
Regularized Linear Programming Discriminant Rule with Folded Concave Penalty for Ultrahigh-Dimensional Data. 1074-1082 - Yuan Gao, Xuening Zhu, Haobo Qi, Guodong Li, Riquan Zhang, Hansheng Wang:
An Asymptotic Analysis of Random Partition Based Minibatch Momentum Methods for Linear Regression Models. 1083-1096 - Alfonso Landeros, Kenneth Lange:
Algorithms for Sparse Support Vector Machines. 1097-1108 - Louis Raynal, Till Hoffmann, Jukka-Pekka Onnela:
Cost-based Feature Selection for Network Model Choice. 1109-1118 - Marzia A. Cremona, Francesca Chiaromonte:
Probabilistic K -means with Local Alignment for Clustering and Motif Discovery in Functional Data. 1119-1130 - Junyi Zhou, Ying Zhang, Wanzhu Tu:
clusterMLD: An Efficient Hierarchical Clustering Method for Multivariate Longitudinal Data. 1131-1144 - Xiran Liu, Naama M. Kopelman, Noah A. Rosenberg:
A Dirichlet Model of Alignment Cost in Mixed-Membership Unsupervised Clustering. 1145-1159 - Chenglong Ye, Reza Ghanadan, Jie Ding:
Meta Clustering for Collaborative Learning. 1160-1169 - Sihan Huang, Haolei Weng, Yang Feng:
Spectral Clustering via Adaptive Layer Aggregation for Multi-Layer Networks. 1170-1184 - Yinqiao Yan, Xiangyu Luo:
Bayesian Tree-Structured Two-Level Clustering for Nested Data Analysis. 1185-1194 - Andrea Cappozzo, Luis Angel García-Escudero, Francesca Greselin, Agustín Mayo-Íscar:
Graphical and Computational Tools to Guide Parameter Choice for the Cluster Weighted Robust Model. 1195-1214 - Luca Greco, Pierluigi Novi Inverardi, Claudio Agostinelli:
Finite Mixtures of Multivariate Wrapped Normal Distributions for Model Based Clustering of p -Torus Data. 1215-1228 - Ursula Laa, Alex Aumann, Dianne Cook, German Valencia:
New and Simplified Manual Controls for Projection and Slice Tours, With Application to Exploring Classification Boundaries in High Dimensions. 1229-1236
Volume 32, Number 4, 2023
- Corinne Jones, Vincent Roulet, Zaïd Harchaoui:
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods. 1237-1247 - Aniruddha Rajendra Rao, Matthew Reimherr:
Nonlinear Functional Modeling Using Neural Networks. 1248-1257 - Shengtong Zhang, Daniel W. Apley:
Interpretable Architecture Neural Networks for Function Visualization. 1258-1271 - Marius Hofert, Avinash Prasad, Mu Zhu:
Dependence Model Assessment and Selection with DecoupleNets. 1272-1286 - Akifumi Okuno, Keisuke Yano:
A Generalization Gap Estimation for Overparameterized Models via the Langevin Functional Variance. 1287-1295 - Tianxi Li, Yun-Jhong Wu, Elizaveta Levina, Ji Zhu:
Link Prediction for Egocentrically Sampled Networks. 1296-1319 - Zhongyuan Lyu, Dong Xia, Yuan Zhang:
Latent Space Model for Higher-Order Networks and Generalized Tensor Decomposition. 1320-1336 - Kris Sankaran:
Bootstrap Confidence Regions for Learned Feature Embeddings. 1337-1347 - Haobo Qi, Feifei Wang, Hansheng Wang:
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator. 1348-1360 - Rosario Barone, Luciana Dalla Valle:
Bayesian Nonparametric Modeling of Conditional Multidimensional Dependence Structures. 1361-1370 - David B. Dahl, Devin J. Johnson, Jacob Andros:
Comparison and Bayesian Estimation of Feature Allocations. 1371-1382 - Harriet Spearing, Jonathan A. Tawn, David Irons, Tim Paulden:
Modeling Intransitivity in Pairwise Comparisons with Application to Baseball Data. 1383-1392 - Benjamin Christoffersen, Behrang Mahjani, Mark Clements, Hedvig Kjellström, Keith Humphreys:
Quasi-Monte Carlo Methods for Binary Event Models with Complex Family Data. 1393-1401 - Andrew J. Holbrook:
A Quantum Parallel Markov Chain Monte Carlo. 1402-1415 - Pierpaolo De Blasi, María F. Gil-Leyva:
Gibbs Sampling for Mixtures in Order of Appearance: The Ordered Allocation Sampler. 1416-1424 - Matthew Sutton, Paul Fearnhead:
Concave-Convex PDMP-based Sampling. 1425-1435 - Chris Sherlock, Szymon Urbas, Matthew Ludkin:
The Apogee to Apogee Path Sampler. 1436-1446 - Alice Martin, Marie-Pierre Étienne, Pierre Gloaguen, Sylvain Le Corff, Jimmy Olsson:
Backward Importance Sampling for Online Estimation of State Space Models. 1447-1460 - Dennis Prangle, Cecilia Viscardi:
Distilling Importance Sampling for Likelihood Free Inference. 1461-1471 - Mitchell Krock, William Kleiber, Dorit Hammerling, Stephen Becker:
Modeling Massive Highly Multivariate Nonstationary Spatial Data with the Basis Graphical Lasso. 1472-1487 - Lorenzo Cappello, Oscar Hernan Madrid Padilla, Julia A. Palacios:
Bayesian Change Point Detection with Spike-and-Slab Priors. 1488-1500 - Tao Li, Jun Yu, Cheng Meng:
Scalable Model-Free Feature Screening via Sliced-Wasserstein Dependency. 1501-1511 - Mengyu Li, Jun Yu, Hongteng Xu, Cheng Meng:
Efficient Approximation of Gromov-Wasserstein Distance Using Importance Sparsification. 1512-1523 - Saptarshi Chakraborty, Jason Q. Xu:
Biconvex Clustering. 1524-1536 - Emily A. Robinson, Reka Howard, Susan VanderPlas:
Eye Fitting Straight Lines in the Modern Era. 1537-1544 - Huang Huang, Ying Sun, Marc G. Genton:
Test and Visualization of Covariance Properties for Multivariate Spatio-Temporal Random Fields. 1545-1555 - Charlie Sire, Rodolphe Le Riche, Didier Rullière, Jérémy Rohmer, Lucie Pheulpin, Yann Richet:
Quantizing Rare Random Maps: Application to Flooding Visualization. 1556-1571 - Susan VanderPlas, Yawei Ge, Antony Unwin, Heike Hofmann:
Penguins Go Parallel: A Grammar of Graphics Framework for Generalized Parallel Coordinate Plots. 1572-1587 - Jiahao Cao, Shiyuan He, Bohai Zhang:
Spatial Linear Regression with Covariate Measurement Errors: Inference and Scalable Computation in a Functional Modeling Approach. 1588-1599 - Almond Stöcker, Lisa Steyer, Sonja Greven:
Functional Additive Models on Manifolds of Planar Shapes and Forms. 1600-1612 - Bo Kai, Mian Huang, Weixin Yao, Yuexiao Dong:
Nonparametric and Semiparametric Quantile Regression via a New MM Algorithm. 1613-1623 - Zhihua Su, Bing Li, R. Dennis Cook:
Envelope Model for Function-on-Function Linear Regression. 1624-1635 - Tonglin Zhang:
Maximum Likelihood Algorithm for Spatial Generalized Linear Mixed Models without Numerical Evaluations of Intractable Integrals. 1636-1648 - Ze Chen, Jun Liao, Wangli Xu, Yuhong Yang:
Multifold Cross-Validation Model Averaging for Generalized Additive Partial Linear Models. 1649-1659 - Elliot Dovers, Wesley Brooks, Gordana C. Popovic, David I. Warton:
Fast, Approximate Maximum Likelihood Estimation of Log-Gaussian Cox Processes. 1660-1670 - Wan-Lun Wang:
Multivariate Contaminated Normal Censored Regression Model: Properties and Maximum Likelihood Inference. 1671-1684 - Tony Sit, Yue Xing:
Distributed Censored Quantile Regression. 1685-1697
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