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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 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 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, Xin Yuan 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 T. 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
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