Journal of Computational and Graphical Statistics

Article	Citations
False Discovery Rates to Detect Signals from Incomplete Spatially Aggregated Data	71
Logistic Regression Models for Aggregated Data	29
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models	28
Adaptive Bayesian Spectral Analysis of High-Dimensional Nonstationary Time Series	25
Branching Process Models to Identify Risk Factors for Infectious Disease Transmission	25
Persistence Flamelets: Topological Invariants for Scale Spaces	25
Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Replicated Time Series	24
Variable Selection and Estimation for Misclassified Binary Responses and Multivariate Error-Prone Predictors	21
Selective Imputation of Covariates in High Dimensional Censored Data	20
Exploiting Disagreement Between High-Dimensional Variable Selectors for Uncertainty Visualization	19
Distributed Learning for Principal Eigenspaces without Moment Constraints	17
Hybrid Kronecker Product Decomposition and Approximation	17
Distance-based Clustering of Functional Data with Derivative Principal Component Analysis	16
Principal Variables Analysis for Non-Gaussian Data	15
Versatile Descent Algorithms for Group Regularization and Variable Selection in Generalized Linear Models	15
Multiple-Use Calibration for All Future Values and Exact Two-Sided Simultaneous Tolerance Intervals in Linear Regression	14
Big Data Model Building Using Dimension Reduction and Sample Selection	14
On Construction and Estimation of Stationary Mixture Transition Distribution Models	13
Stability Approach to Regularization Selection for Reduced-Rank Regression	13
Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data	13
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	12
Parameter Estimation of Binned Hawkes Processes	12
Robust Multivariate Lasso Regression with Covariance Estimation	12
Statistically Valid Variational Bayes Algorithm for Ising Model Parameter Estimation	11
Gibbs Priors for Bayesian Nonparametric Variable Selection with Weak Learners	11

Burning Sage: Reversing the Curse of Dimensionality in the Visualization of High-Dimensional Data	11
Functional Nonlinear Learning	11
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model	11
Scalable Estimation for Structured Additive Distributional Regression	10
Fast Forecast Reconciliation Using Linear Models	10
MCMC Algorithms for Posteriors on Matrix Spaces	10
Globally Centered Autocovariances in MCMC	9
Online Updating of Survival Analysis	9
Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives	9
Joint Modeling of Longitudinal Imaging and Survival Data	9
GEE-Assisted Forward Regression for Spatial Latent Variable Models	9
Generalized Tensor Decomposition With Features on Multiple Modes	9
Eigenvectors from Eigenvalues Sparse Principal Component Analysis	9
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference	8
Sequential Learning of Regression Models by Penalized Estimation	8
The Holdout Randomization Test for Feature Selection in Black Box Models	8
Efficient estimation of parameters in marginals in semiparametric multivariate models*	8
AutoGFI: Streamlined Generalized Fiducial Inference for Modern Inference Problems in Models with Additive Errors	7
Variational Inference based on a Subclass of Closed Skew Normals	7
High-Dimensional Block Diagonal Covariance Structure Detection Using Singular Vectors	7
Bayesian Partial Reduced-Rank Regression	7
Dimension Reduction Forests: Local Variable Importance Using Structured Random Forests	7
Distributed Bayesian Inference in Linear Mixed-Effects Models	7
flexBART: Flexible Bayesian Regression Trees with Categorical Predictors	7
Bayesian Pairwise Comparison of High-Dimensional Images	7
Network Embedding-based Directed Community Detection with Unknown Community Number	7
Heterogeneous Functional Regression for Subgroup Analysis	7
Simultaneous Estimation of Multiple Treatment Effects from Observational Studies	7
Group-Orthogonal Subsampling for Hierarchical Data Based on Linear Mixed Models	6
Double Probability Integral Transform Residuals for Regression Models with Discrete Outcomes	6
Regularized Linear Programming Discriminant Rule with Folded Concave Penalty for Ultrahigh-Dimensional Data	6
Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization	6
Fast Multilevel Functional Principal Component Analysis	6
Exactly Uncorrelated Sparse Principal Component Analysis	6
Analytic Permutation Testing for Functional Data ANOVA	6
A Bayesian Collocation Integral Method for Parameter Estimation in Ordinary Differential Equations	6
Adaptive Wavelet Domain Principal Component Analysis for Nonstationary Time Series	6
Properties of Test Statistics for Nonparametric Cointegrating Regression Functions Based on Subsamples	6
Generative Multi-Purpose Sampler for Weighted M-estimation	6
Local Clustering for Functional Data	5
Fast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models	5
Maximum Likelihood Algorithm for Spatial Generalized Linear Mixed Models without Numerical Evaluations of Intractable Integrals	5
Test and Visualization of Covariance Properties for Multivariate Spatio-Temporal Random Fields	5
Latent Markov Time-Interaction Processes	5
High-Dimensional Multivariate Linear Regression with Weighted Nuclear Norm Regularization	5
A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices	5
Finite Mixtures of Multivariate Wrapped Normal Distributions for Model Based Clustering of p -Torus Data	5
Scalable Clustering: Large Scale Unsupervised Learning of Gaussian Mixture Models with Outliers	5
Interpretable Architecture Neural Networks for Function Visualization	5
Modeling Massive Highly Multivariate Nonstationary Spatial Data with the Basis Graphical Lasso	5

Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model	5
A Multi-Attribute Evaluation of Genotype-Environment Experiments Using Biplots and Joint Plots Graphics	5
Nonparametric High-Dimensional Multi-Sample Tests based on Graph Theory	5
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods	5
Efficient Sampling From the Watson Distribution in Arbitrary Dimensions	5
A Generalization Gap Estimation for Overparameterized Models via the Langevin Functional Variance	5
Estimating the Hawkes process from a discretely observed sample path	5
Structured Variational Approximations with Skew Normal Decomposable Graphical Models and Implicit Copulas	5
MFAI: A Scalable Bayesian Matrix Factorization Approach to Leveraging Auxiliary Information	5
Computational Methods for Fast Bayesian Model Assessment via Calibrated Posterior p -values	4
Randomized Spectral Clustering in Large-Scale Stochastic Block Models	4
Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression	4
Varying Coefficient Model via Adaptive Spline Fitting	4
Standardized Partial Sums and Products of p-Values	4
Sparse Functional Boxplots for Multivariate Curves	4
Supervised Stratified Subsampling for Predictive Analytics	4
An Interpretable Neural Network-based Nonproportional Odds Model for Ordinal Regression	4
Fast Calculation of Gaussian Process Multiple-Fold Cross-Validation Residuals and their Covariances	4
Dynamic Prediction Using Landmark Historical Functional Cox Regression	4
Zig-Zag Sampling for Discrete Structures and Nonreversible Phylogenetic MCMC	4
Quasi-Newton Acceleration of EM and MM Algorithms via Broyden’s Method	4
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings	4
Stochastic Block Smooth Graphon Model	4
Finite-Sample Two-Group Composite Hypothesis Testing via Machine Learning	4
Estimation and Selection for High-Order Markov Chains with Bayesian Mixture Transition Distribution Models	4
Graphical Influence Diagnostics for Changepoint Models	4
Visualization for Interval Data	4
Functional Time Series Analysis and Visualization Based on Records	4
Triangular Concordance Learning of Networks	4
Testing Model Specification in Approximate Bayesian Computation Using Asymptotic Properties	4
TSLiNGAM: DirectLiNGAM Under Heavy Tails	4
A Distributed Block-Split Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems	4
Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference	3
Fast and Separable Estimation in High-Dimensional Tensor Gaussian Graphical Models	3
Functional Projection K -means	3
Robust Transformations for Multiple Regression via Additivity and Variance Stabilization	3
Integrated Depths for Partially Observed Functional Data	3
Implicit Copula Variational Inference	3
Fast and Scalable Algorithm for Detection of Structural Breaks in Big VAR Models	3
High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference	3
Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance	3
Sample-Wise Combined Missing Effect Model with Penalization	3
Improving and Extending STERGM Approximations Based on Cross-Sectional Data and Tie Durations	3
Random Forest Adjustment for Approximate Bayesian Computation	3
Structured Shrinkage Priors	3
Co-Factor Analysis of Citation Networks	3
Approximating Partial Likelihood Estimators via Optimal Subsampling	3
Iteratively Reweighted Least Squares Method for Estimating Polyserial and Polychoric Correlation Coefficients	3
Asynchronous and Distributed Data Augmentation for Massive Data Settings	3
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory	3
Visualization and Assessment of Copula Symmetry	3
Model Selection With Lasso-Zero: Adding Straw to the Haystack to Better Find Needles	3
Leave-One-Out Kernel Density Estimates for Outlier Detection	3
Log-Rank-Type Tests for Equality of Distributions in High-Dimensional Spaces	3
Bayesian Computation in Dynamic Latent Factor Models	3
Variable Selection for High-Dimensional Heteroscedastic Regression and Its Applications	3
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers	3
Data Integration with Oracle Use of External Information from Heterogeneous Populations	3
Multiway Sparse Distance Weighted Discrimination	3
Reproducible Hyperparameter Optimization	3
Importance Sampling-Based Transport Map Hamiltonian Monte Carlo for Bayesian Hierarchical Models	3
Model-Based Microbiome Data Ordination: A Variational Approximation Approach	3
A Unified Approach to Variable Selection for Partially Linear Models	3
Fully Three-Dimensional Radial Visualization	2
Communication-Efficient Nonparametric Quantile Regression via Random Features	2
Fast, Approximate Maximum Likelihood Estimation of Log-Gaussian Cox Processes	2
Scalable Model-Free Feature Screening via Sliced-Wasserstein Dependency	2
Gibbs Sampling for Mixtures in Order of Appearance: The Ordered Allocation Sampler	2
The Apogee to Apogee Path Sampler	2
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data	2
Mutually Exciting Point Process Graphs for Modeling Dynamic Networks	2
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation	2
On the Use of Minimum Penalties in Statistical Learning	2
d-blink: Distributed End-to-End Bayesian Entity Resolution	2
Distortion Corrected Kernel Density Estimator on Riemannian Manifolds	2
Using Rejection Sampling Probability of Acceptance as a Measure of Independence	2
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies	2
Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty	2
Low-rank, Orthogonally Decomposable Tensor Regression With Application to Visual Stimulus Decoding of fMRI Data	2
Grid Point Approximation for Distributed Nonparametric Smoothing and Prediction	2

A Latent Space Model for Weighted Keyword Co-Occurrence Networks with Applications in Knowledge Discovery in Statistics	2
The Chi-Square Test of Distance Correlation	2
Biconvex Clustering	2
Multivariate Contaminated Normal Censored Regression Model: Properties and Maximum Likelihood Inference	2
Quantizing Rare Random Maps: Application to Flooding Visualization	2
Pseudo-Marginal Inference for CTMCs on Infinite Spaces via Monotonic Likelihood Approximations	2
Distributed Censored Quantile Regression	2
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series	2
Least-Square Approximation for a Distributed System	2
Inference and Computation for Sparsely Sampled Random Surfaces	2
MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes	2
Multi-label Random Subspace Ensemble Classification	2
Efficient Modeling of Spatial Extremes over Large Geographical Domains	2
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	2
Generative Quantile Regression with Variability Penalty	2
Multivariate Functional Regression Via Nested Reduced-Rank Regularization	2
Micro–Macro Changepoint Inference for Periodic Data Sequences	2
Decentralized Learning of Quantile Regression: a Smoothing Approach	2
The q–q Boxplot	2
Bayesian Nonparametric Modeling of Conditional Multidimensional Dependence Structures	2
Backward Importance Sampling for Online Estimation of State Space Models	2
Eye Fitting Straight Lines in the Modern Era	2
Multivariate quantile-based permutation tests with application to functional data	2
Mixture of Linear Models Co-supervised by Deep Neural Networks	2
Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code	2
An Extension of the Unified Skew-Normal Family of Distributions and its Application to Bayesian Binary Regression	2
Matrix Autoregressive Spatio-Temporal Models	2
Massive Parallelization of Massive Sample-Size Survival Analysis	2
Nonstationary Spatial Modeling of Massive Global Satellite Data	2
Functional Mixed Membership Models	2
Latent Space Model for Higher-Order Networks and Generalized Tensor Decomposition	2
On Inference for Modularity Statistics in Structured Networks	1
A Stochastic Approximation-Langevinized Ensemble Kalman Filter Algorithm for State Space Models with Unknown Parameters	1
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	1
Learning Subspaces of Different Dimensions	1
Variable Screening for Sparse Online Regression	1
Interactive Slice Visualization for Exploring Machine Learning Models	1
Practical Network Modeling via Tapered Exponential-Family Random Graph Models	1
Fast Community Detection in Dynamic and Heterogeneous Networks	1
Eigen-Adjusted Functional Principal Component Analysis	1
Bayesian Kernel Two-Sample Testing	1
Fast Computation of Latent Correlations	1
Simultaneous Semiparametric Estimation of Clustering and Regression	1
A General Framework for Identifying Hierarchical Interactions and Its Application to Genomics Data	1
Simultaneous Coefficient Clustering and Sparsity for Multivariate Mixed Models	1
Analysis of Professional Basketball Field Goal Attempts via a Bayesian Matrix Clustering Approach	1
Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference	1
Silhouettes and Quasi Residual Plots for Neural Nets and Tree-based Classifiers	1
Loss-Based Variational Bayes Prediction	1
Variable selection and basis learning for ordinal classification	1
Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks	1
An Exact Game-Theoretic Variable Importance Index for Generalized Additive Models	1
A Reproducing Kernel Hilbert Space Framework for Functional Classification	1
Bayesian Nowcasting with Laplacian-P-Splines	1
Statistical Analysis of Locally Parameterized Shapes	1
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	1
Exhaustive Goodness of Fit Via Smoothed Inference and Graphics	1
Visualizing Probability Distributions Across Bivariate Cyclic Temporal Granularities	1
A Single-Index Model With a Surface-Link for Optimizing Individualized Dose Rules	1
Fast Univariate Inference for Longitudinal Functional Models	1
Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty	1
Enforcing Stationarity through the Prior in Vector Autoregressions	1
Sequential Learning of Active Subspaces	1
Bootstrapped Edge Count Tests for Nonparametric Two-Sample Inference Under Heterogeneity	1
A Distribution-Free Method for Change Point Detection in Non-Sparse High Dimensional Data	1
Manifold Optimization-Assisted Gaussian Variational Approximation	1
Sensitivity Analysis of Pandemic Models Can Support Effective Policy Decisions	1
Extrapolation before imputation reduces bias when imputing censored covariates	1
Ultra-Efficient MCMC for Bayesian Longitudinal Functional Data Analysis	1
No More, No Less than Sum of Its Parts: Groups, Monoids, and the Algebra of Graphics, Statistics, and Interaction	1
Projected Pólya Tree	1
Scalable Estimation and Two-Sample Testing for Large Networks via Subsampling	1
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks	1
Dynamic Survival Prediction Using Sparse Longitudinal Images via Multi-Dimensional Functional Principal Component Analysis	1
Meta Clustering for Collaborative Learning	1
On Data Augmentation for Models Involving Reciprocal Gamma Functions	1
Copulas and Histogram-Valued Data	1
Scalable Computation of Predictive Probabilities in Probit Models with Gaussian Process Priors	1
Bayesian L 1/2 Regression	1
Cost-based Feature Selection for Network Model Choice	1
The Journal of Computational and Graphical Statistics 2023 Associate Editors	1
Computationally Efficient Learning of Gaussian Linear Structural Equation Models with Equal Error Variances	1
Assessment of Regression Models With Discrete Outcomes Using Quasi-Empirical Residual Distribution Functions	1
A Bayesian Singular Value Decomposition Procedure for Missing Data Imputation	1
Bayesian Semiparametric Covariate Informed Multivariate Density Deconvolution	1
Global Inference and Test for Eigensystems of Imaging Data Over Complicated Domains	1
Fast Bayesian Inference for Spatial Mean-Parameterized Conway–Maxwell–Poisson Models	1
Search Algorithms and Loss Functions for Bayesian Clustering	1
Optimal Integrating Learning for Split Questionnaire Design Type Data	1
Optimal Decorrelated Score Subsampling for High-Dimensional Generalized Linear Models Under Measurement Constraints	1
Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes	1
Sparse Model-Based Clustering of Three-Way Data via Lasso-Type Penalties	1
The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC	1
Dynamic Supervised Principal Component Analysis for Classification	1
A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data	1