Journal of Computational and Graphical Statistics

Article	Citations
Multiple-Use Calibration for All Future Values and Exact Two-Sided Simultaneous Tolerance Intervals in Linear Regression	49
Distance-based Clustering of Functional Data with Derivative Principal Component Analysis	35
Principal Variables Analysis for Non-Gaussian Data	34
Efficient Estimation of Parameters in Marginals in Semiparametric Multivariate Models	34
Distributed Learning for Principal Eigenspaces without Moment Constraints	31
Estimating the Hawkes Process From a Discretely Observed Sample Path	28
Bayesian Partial Reduced-Rank Regression	27
Persistence Flamelets: Topological Invariants for Scale Spaces	24
Selective Imputation of Covariates in High Dimensional Censored Data	22
Sensitivity Analysis for Binary Outcome Misclassification in Randomization Tests via Integer Programming	20
A Deep Dynamic Latent Block Model for Co-clustering of Zero-Inflated Data Matrices	20
An Interpretable Neural Network-based Nonproportional Odds Model for Ordinal Regression	19
Quantile Regression and Homogeneity Identification of a Semiparametric Panel Data Model	17
Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Replicated Time Series	16
Branching Process Models to Identify Risk Factors for Infectious Disease Transmission	16
Exploiting Disagreement Between High-Dimensional Variable Selectors for Uncertainty Visualization	15
Hybrid Kronecker Product Decomposition and Approximation	14
Sequential Learning of Regression Models by Penalized Estimation	13
Robust Multivariate Lasso Regression with Covariance Estimation	13
Test and Visualization of Covariance Properties for Multivariate Spatio-Temporal Random Fields	12
Globally Centered Autocovariances in MCMC	12
Gibbs Priors for Bayesian Nonparametric Variable Selection with Weak Learners	12
MCMC Algorithms for Posteriors on Matrix Spaces	12
High-Dimensional Block Diagonal Covariance Structure Detection Using Singular Vectors	11
Local Clustering for Functional Data	11

AutoGFI: Streamlined Generalized Fiducial Inference for Modern Inference Problems in Models with Additive Errors	11
flexBART: Flexible Bayesian Regression Trees with Categorical Predictors	11
Bayesian Pairwise Comparison of High-Dimensional Images	11
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference	10
Eigenvectors from Eigenvalues Sparse Principal Component Analysis	10
The Holdout Randomization Test for Feature Selection in Black Box Models	10
Regularized Linear Programming Discriminant Rule with Folded Concave Penalty for Ultrahigh-Dimensional Data	10
Simultaneous Estimation of Multiple Treatment Effects from Observational Studies	10
Variational Inference based on a Subclass of Closed Skew Normals	9
Exactly Uncorrelated Sparse Principal Component Analysis	9
Statistically Valid Variational Bayes Algorithm for Ising Model Parameter Estimation	9
Nonparametric High-Dimensional Multi-Sample Tests based on Graph Theory	9
Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives	9
Dimension Reduction Forests: Local Variable Importance Using Structured Random Forests	9
A Multi-Attribute Evaluation of Genotype-Environment Experiments Using Biplots and Joint Plots Graphics	9
MFAI: A Scalable Bayesian Matrix Factorization Approach to Leveraging Auxiliary Information	8
Big Data Model Building Using Dimension Reduction and Sample Selection	8
Scalable Estimation for Structured Additive Distributional Regression	8
Burning Sage: Reversing the Curse of Dimensionality in the Visualization of High-Dimensional Data	8
Generative Multi-Purpose Sampler for Weighted M-estimation	8
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	7
Interpretable Architecture Neural Networks for Function Visualization	7
Adaptive Wavelet Domain Principal Component Analysis for Nonstationary Time Series	7
High-Dimensional Multivariate Linear Regression with Weighted Nuclear Norm Regularization	7
Group-Orthogonal Subsampling for Hierarchical Data Based on Linear Mixed Models	7
Structured Variational Approximations with Skew Normal Decomposable Graphical Models and Implicit Copulas	7
GEE-Assisted Forward Regression for Spatial Latent Variable Models	6
Revisiting Convolutional Neural Networks from the Viewpoint of Kernel-Based Methods	6
Double Probability Integral Transform Residuals for Regression Models with Discrete Outcomes	6
Analytic Permutation Testing for Functional Data ANOVA	6
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model	6
Fast Forecast Reconciliation Using Linear Models	6
Stability Approach to Regularization Selection for Reduced-Rank Regression	6
A Bayesian Collocation Integral Method for Parameter Estimation in Ordinary Differential Equations	6
A Generalization Gap Estimation for Overparameterized Models via the Langevin Functional Variance	6
Perception and Cognitive Implications of Logarithmic Scales for Exponentially Increasing Data: Perceptual Sensitivity Tested with Statistical Lineups	5
Efficient Sampling From the Watson Distribution in Arbitrary Dimensions	5
Properties of Test Statistics for Nonparametric Cointegrating Regression Functions Based on Subsamples	5
Generalized Tensor Decomposition With Features on Multiple Modes	5
Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization	5
On Construction and Estimation of Stationary Mixture Transition Distribution Models	5
Functional Nonlinear Learning	5
Modeling Massive Highly Multivariate Nonstationary Spatial Data with the Basis Graphical Lasso	5
A Cepstral Model for Efficient Spectral Analysis of Covariate-dependent Time Series	5
Scalable Clustering: Large Scale Unsupervised Learning of Gaussian Mixture Models with Outliers	5
Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data	5
Network Embedding-based Directed Community Detection with Unknown Community Number	5
Versatile Descent Algorithms for Group Regularization and Variable Selection in Generalized Linear Models	5
Variable Selection and Estimation for Misclassified Binary Responses and Multivariate Error-Prone Predictors	5
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models	5

Fast Multilevel Functional Principal Component Analysis	5
Joint Modeling of Longitudinal Imaging and Survival Data	5
Maximum Likelihood Algorithm for Spatial Generalized Linear Mixed Models without Numerical Evaluations of Intractable Integrals	5
Finite Mixtures of Multivariate Wrapped Normal Distributions for Model Based Clustering of p -Torus Data	5
Fast, Scalable Approximations to Posterior Distributions in Extended Latent Gaussian Models	5
Latent Markov Time-Interaction Processes	5
Heterogeneous Functional Regression for Subgroup Analysis	5
Parameter Estimation of Binned Hawkes Processes	5
Logistic Regression Models for Aggregated Data	5
Triangular Concordance Learning of Networks	4
Variable Selection for High-Dimensional Heteroscedastic Regression and Its Applications	4
Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty	4
Sparse Functional Boxplots for Multivariate Curves	4
Biconvex Clustering	4
Biplots for the correlation matrix	4
Standardized Partial Sums and Products of p-Values	4
Visualization for Interval Data	4
Functional Time Series Analysis and Visualization Based on Records	4
Bayesian Computation in Dynamic Latent Factor Models	4
Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression	4
Eye Fitting Straight Lines in the Modern Era	4
Dynamic Prediction Using Landmark Historical Functional Cox Regression	4
Zig-Zag Sampling for Discrete Structures and Nonreversible Phylogenetic MCMC	4
Leave-One-Out Kernel Density Estimates for Outlier Detection	4
High-Dimensional Covariate-Dependent Gaussian Graphical Models	4
Integrated Depths for Partially Observed Functional Data	4
Fast, Approximate Maximum Likelihood Estimation of Log-Gaussian Cox Processes	4
Stochastic Block Smooth Graphon Model	4
Implicit Copula Variational Inference	3
Data Integration with Oracle Use of External Information from Heterogeneous Populations	3
Log-Rank-Type Tests for Equality of Distributions in High-Dimensional Spaces	3
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings	3
Quantizing Rare Random Maps: Application to Flooding Visualization	3
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	3
Computational Methods for Fast Bayesian Model Assessment via Calibrated Posterior p -values	3
Improving and Extending STERGM Approximations Based on Cross-Sectional Data and Tie Durations	3
Clustering Time-Evolving Networks Using Temporal Exponential-Family Random Graph Models with Conditional Dyadic Independence and Dynamic Latent Blocks*	3
Sample-Wise Combined Missing Effect Model with Penalization	3
Graphical Influence Diagnostics for Changepoint Models	3
Supervised Stratified Subsampling for Predictive Analytics	3
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation	3
Co-Factor Analysis of Citation Networks	3
Fast and Scalable Algorithm for Detection of Structural Breaks in Big VAR Models	3
Functional Mixed Membership Models	3
Asynchronous and Distributed Data Augmentation for Massive Data Settings	3
Approximating Partial Likelihood Estimators via Optimal Subsampling	3
Quasi-Newton Acceleration of EM and MM Algorithms via Broyden’s Method	3
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data	3
A Unified Approach to Variable Selection for Partially Linear Models	3
Importance Sampling-Based Transport Map Hamiltonian Monte Carlo for Bayesian Hierarchical Models	3
Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code	3
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory	3
Nonstationary Spatial Modeling of Massive Global Satellite Data	3
Robust Transformations for Multiple Regression via Additivity and Variance Stabilization	3
Functional Projection K -means	3
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers	3
Multiway Sparse Distance Weighted Discrimination	3
Distributed Censored Quantile Regression	3
Bayesian Nonparametric Modeling of Conditional Multidimensional Dependence Structures	3
Random Forest Adjustment for Approximate Bayesian Computation	3
MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes	3
Gibbs Sampling for Mixtures in Order of Appearance: The Ordered Allocation Sampler	3
Matrix Autoregressive Spatio-Temporal Models	3
Randomized Spectral Clustering in Large-Scale Stochastic Block Models	3
Decentralized Learning of Quantile Regression: A Smoothing Approach	3
Visualization and Assessment of Copula Symmetry	2
Distortion Corrected Kernel Density Estimator on Riemannian Manifolds	2
Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference	2
Bayesian Nowcasting with Laplacian-P-Splines	2
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies	2
The q–q Boxplot	2
Least-Square Approximation for a Distributed System	2
Optimal Decorrelated Score Subsampling for High-Dimensional Generalized Linear Models Under Measurement Constraints	2
Fast Matrix-Free Methods for Model-Based Personalized Synthetic MR Imaging	2
Inference and Computation for Sparsely Sampled Random Surfaces	2
Massive Parallelization of Massive Sample-Size Survival Analysis	2
Convergence of Position-Dependent MALA with Application to Conditional Simulation in GLMMs	2
Varying Coefficient Model via Adaptive Spline Fitting	2
Generative Quantile Regression with Variability Penalty	2
A Distributed Block-Split Gibbs Sampler with Hypergraph Structure for High-Dimensional Inverse Problems	2

Estimation and Selection for High-Order Markov Chains with Bayesian Mixture Transition Distribution Models	2
Fast Calculation of Gaussian Process Multiple-Fold Cross-Validation Residuals and their Covariances	2
Multivariate Quantile-Based Permutation Tests with Application to Functional Data	2
Reproducible Hyperparameter Optimization	2
Extrapolation Before Imputation Reduces Bias When Imputing Censored Covariates	2
Dynamic Supervised Principal Component Analysis for Classification	2
Computationally Efficient Learning of Gaussian Linear Structural Equation Models with Equal Error Variances	2
Optimal Integrating Learning for Split Questionnaire Design Type Data	2
Finite-Sample Two-Group Composite Hypothesis Testing via Machine Learning	2
Micro–Macro Changepoint Inference for Periodic Data Sequences	2
Model-Based Tensor Low-Rank Clustering	2
An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model	2
Structured Shrinkage Priors	2
Popularity Adjusted Block Models are Generalized Random Dot Product Graphs	2
High-Dimensional Multi-Task Learning using Multivariate Regression and Generalized Fiducial Inference	2
A Latent Space Model for Weighted Keyword Co-Occurrence Networks with Applications in Knowledge Discovery in Statistics	2
Communication-Efficient Nonparametric Quantile Regression via Random Features	2
On Inference for Modularity Statistics in Structured Networks	2
Fast and Separable Estimation in High-Dimensional Tensor Gaussian Graphical Models	2
Fast Bayesian Inference for Spatial Mean-Parameterized Conway–Maxwell–Poisson Models	2
Iteratively Reweighted Least Squares Method for Estimating Polyserial and Polychoric Correlation Coefficients	2
Fast Computer Model Calibration using Annealed and Transformed Variational Inference	2
Efficient Modeling of Spatial Extremes over Large Geographical Domains	2
Cost-based Feature Selection for Network Model Choice	2
Template Independent Component Analysis with Spatial Priors for Accurate Subject-Level Brain Network Estimation and Inference	2
Dynamic Survival Prediction Using Sparse Longitudinal Images via Multi-Dimensional Functional Principal Component Analysis	2
On the Use of Minimum Penalties in Statistical Learning	2
Scalable Computation of Predictive Probabilities in Probit Models with Gaussian Process Priors	2
Testing Model Specification in Approximate Bayesian Computation Using Asymptotic Properties	2
Using Rejection Sampling Probability of Acceptance as a Measure of Independence	2
TSLiNGAM: DirectLiNGAM Under Heavy Tails	2
An Exact Game-Theoretic Variable Importance Index for Generalized Additive Models	2
Efficient Convex PCA with Applications to Wasserstein GPCA and Ranked Data	1
Enforcing Stationarity through the Prior in Vector Autoregressions	1
Distilling Importance Sampling for Likelihood Free Inference	1
Lessons from West Virginia’s Pandemic Response	1
Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization	1
The Chi-Square Test of Distance Correlation	1
Change Point Detection in Dynamic Networks via Regularized Tensor Decomposition	1
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	1
Adaptive Preferential Sampling in Phylodynamics With an Application to SARS-CoV-2	1
Latent Space Model for Higher-Order Networks and Generalized Tensor Decomposition	1
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	1
Method G: Uncertainty Quantification for Distributed Data Problems Using Generalized Fiducial Inference	1
Partition-Based Nonstationary Covariance Estimation Using the Stochastic Score Approximation	1
Improved Pathwise Coordinate Descent for Power Penalties	1
Is this normal? A new projection pursuit index to assess a sample against a multivariate null distribution	1
A Single-Index Model With a Surface-Link for Optimizing Individualized Dose Rules	1
Data Nuggets: A Method for Reducing Big Data While Preserving Data Structure	1
Clustering Sequence Data with Mixture Markov Chains with Covariates Using Multiple Simplex Constrained Optimization Routine (MSiCOR)	1
Relative Entropy Gradient Sampler for Unnormalized Distribution	1
Assessment of Regression Models With Discrete Outcomes Using Quasi-Empirical Residual Distribution Functions	1
A Reproducing Kernel Hilbert Space Framework for Functional Classification	1
Mixture of Linear Models Co-supervised by Deep Neural Networks	1
Population Quasi-Monte Carlo	1
Variable Screening for Sparse Online Regression	1
Semi-Complete Data Augmentation for Efficient State Space Model Fitting	1
Pseudo-Marginal Inference for CTMCs on Infinite Spaces via Monotonic Likelihood Approximations	1
Confidence Bands for a Log-Concave Density	1
Global Inference and Test for Eigensystems of Imaging Data Over Complicated Domains	1
Efficient Nonparametric Estimation of 3D Point Cloud Signals through Distributed Learning	1
Smooth Multi-Period Forecasting With Application to Prediction of COVID-19 Cases	1
Variable selection and basis learning for ordinal classification	1
A General Framework for Identifying Hierarchical Interactions and Its Application to Genomics Data	1
Fast Univariate Inference for Longitudinal Functional Models	1
Sparse Model-Based Clustering of Three-Way Data via Lasso-Type Penalties	1
Search Algorithms and Loss Functions for Bayesian Clustering	1
Sample Efficient Nonparametric Regression via Low-Rank Regularization	1
Multivariate Functional Regression Via Nested Reduced-Rank Regularization	1
Smoothing Splines for Discontinuous Signals	1
A Projection Approach to Local Regression with Variable-Dimension Covariates	1
Bayesian Kernel Two-Sample Testing	1
Multivariate Singular Spectrum Analysis by Robust Diagonalwise Low-Rank Approximation	1
Statistical Analysis of Locally Parameterized Shapes	1
Wavelet Feature Screening	1
Eigen-Adjusted Functional Principal Component Analysis	1
The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC	1
Sensitivity Analysis of Pandemic Models Can Support Effective Policy Decisions	1
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator	1
Multivariate Contaminated Normal Censored Regression Model: Properties and Maximum Likelihood Inference	1
Comparing Two Samples Through Stochastic Dominance: A Graphical Approach	1
Grid Point Approximation for Distributed Nonparametric Smoothing and Prediction	1
More Powerful Selective Inference for the Graph Fused Lasso	1
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series	1
Multiplex Depth for Network-valued Data and Applications	1
Multi-label Random Subspace Ensemble Classification	1
Analysis of Professional Basketball Field Goal Attempts via a Bayesian Matrix Clustering Approach	1
Measure of Strength of Evidence for Visually Observed Differences between Subpopulations	1
Latent Network Estimation and Variable Selection for Compositional Data Via Variational EM	1
No More, No Less than Sum of Its Parts: Groups, Monoids, and the Algebra of Graphics, Statistics, and Interaction	1
Interval-Censored Linear Quantile Regression	1
Linear Aggregation in Tree-Based Estimators	1
Kernel Angle Dependence Measures in Metric Spaces	1
Bayesian Semiparametric Covariate Informed Multivariate Density Deconvolution	1
Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model	1