OOIR: Observatory of International Research

Papers

(The TQCC of Journal of Computational and Graphical Statistics is 3. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)

Article	Citations
Trimmed Constrained Mixed Effects Models: Formulations and Algorithms	56
Automated Redistricting Simulation Using Markov Chain Monte Carlo	36
Local Linear Forests	30
Anomaly Detection in High-Dimensional Data	25
Building Representative Matched Samples With Multi-Valued Treatments in Large Observational Studies	24
The Chi-Square Test of Distance Correlation	23
Efficient Sampling and Structure Learning of Bayesian Networks	23
Survival Regression with Accelerated Failure Time Model in XGBoost	22
LowCon: A Design-based Subsampling Approach in a Misspecified Linear Model	21
Model Interpretation Through Lower-Dimensional Posterior Summarization	18
Least-Square Approximation for a Distributed System	17
Forward Event-Chain Monte Carlo: Fast Sampling by Randomness Control in Irreversible Markov Chains	17
Learning Multiple Quantiles With Neural Networks	16
Data Integration with Oracle Use of External Information from Heterogeneous Populations	15
Search Algorithms and Loss Functions for Bayesian Clustering	15
Robust Approximate Bayesian Inference With Synthetic Likelihood	14
Optimal Sampling for Generalized Linear Models Under Measurement Constraints	14
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models	14
Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and Its Variance Estimate	14
Massive Parallelization Boosts Big Bayesian Multidimensional Scaling	13
Additive Functional Cox Model	13
Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering	13
Mixtures of Matrix-Variate Contaminated Normal Distributions	13
Fast Cross-validation for Multi-penalty High-dimensional Ridge Regression	13
Predictive Distribution Modeling Using Transformation Forests	13

Nonlinear Variable Selection via Deep Neural Networks	12
Randomized Spectral Clustering in Large-Scale Stochastic Block Models	12
Bayesian Optimization Via Barrier Functions	12
Fast Univariate Inference for Longitudinal Functional Models	12
Rapid Bayesian Inference for Expensive Stochastic Models	10
d-blink: Distributed End-to-End Bayesian Entity Resolution	10
Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods	10
The Holdout Randomization Test for Feature Selection in Black Box Models	10
Rerandomization Strategies for Balancing Covariates Using Pre-Experimental Longitudinal Data	9
Change-Point Detection for Graphical Models in the Presence of Missing Values	9
Subset Multivariate Collective and Point Anomaly Detection	9
Latent Network Estimation and Variable Selection for Compositional Data Via Variational EM	9
Global Consensus Monte Carlo	9
Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms	9
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	9
Bayesian Variable Selection for Gaussian Copula Regression Models	8
Scalable Algorithms for Large Competing Risks Data	8
Fast and Separable Estimation in High-Dimensional Tensor Gaussian Graphical Models	8
Smoothing Splines Approximation Using Hilbert Curve Basis Selection	8
Adaptive Bayesian SLOPE: Model Selection With Incomplete Data	8
Model Checking for Hidden Markov Models	8
Vecchia-Approximated Deep Gaussian Processes for Computer Experiments	8
Multi-Resolution Filters for Massive Spatio-Temporal Data	8
Marginally Calibrated Deep Distributional Regression	7
Dependent Modeling of Temporal Sequences of Random Partitions	7
A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data	7
Fast Computation of Latent Correlations	7
Multiple Imputation Through XGBoost	7
Logistic Regression Models for Aggregated Data	7
Nonparametric Anomaly Detection on Time Series of Graphs	7
Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks	7
Identifying Heterogeneous Effect Using Latent Supervised Clustering With Adaptive Fusion	7
A Slice Tour for Finding Hollowness in High-Dimensional Data	7
Generalized Spatially Varying Coefficient Models	7
Deep Learning With Functional Inputs	7
Efficient Bayesian Synthetic Likelihood With Whitening Transformations	7
MIP-BOOST: Efficient and Effective L₀ Feature Selection for Linear Regression	7
Sequential Learning of Active Subspaces	7
TheG-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models	7
Online Updating of Survival Analysis	7
Delayed Acceptance ABC-SMC	6
Penalized Quantile Regression for Distributed Big Data Using the Slack Variable Representation	6
Eigenvectors from Eigenvalues Sparse Principal Component Analysis	6
Importance Sampling with the Integrated Nested Laplace Approximation	6
Nonlinear Functional Modeling Using Neural Networks	6
Model-Based Microbiome Data Ordination: A Variational Approximation Approach	6
Distributed Bayesian Inference in Linear Mixed-Effects Models	6
Nonstationary Modeling With Sparsity for Spatial Data via the Basis Graphical Lasso	6
Likelihood Evaluation of Jump-Diffusion Models Using Deterministic Nonlinear Filters	6
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation	6

Illumination Depth	5
Manifold Optimization-Assisted Gaussian Variational Approximation	5
Reproducible Hyperparameter Optimization	5
Bayesian Spatial Clustering of Extremal Behavior for Hydrological Variables	5
Integrated Depths for Partially Observed Functional Data	5
Cluster Optimized Proximity Scaling	5
Scalable Computation of Predictive Probabilities in Probit Models with Gaussian Process Priors	5
Estimating Multiple Precision Matrices With Cluster Fusion Regularization	5
Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance	5
Two-Dimensional Functional Principal Component Analysis for Image Feature Extraction	5
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference	5
A Projection Pursuit Forest Algorithm for Supervised Classification	5
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	5
Zig-Zag Sampling for Discrete Structures and Nonreversible Phylogenetic MCMC	5
Shrinking the Covariance Matrix Using Convex Penalties on the Matrix-Log Transformation	5
MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes	5
Clustering and Prediction With Variable Dimension Covariates	5
Generalized Tensor Decomposition With Features on Multiple Modes	5
Monte Carlo Simulation on the Stiefel Manifold via Polar Expansion	4
Markov Chain Importance Sampling—A Highly Efficient Estimator for MCMC	4
Modeling Nonstationary Extreme Dependence With Stationary Max-Stable Processes and Multidimensional Scaling	4
Forward Stepwise Deep Autoencoder-Based Monotone Nonlinear Dimensionality Reduction Methods	4
MCVIS: A New Framework for Collinearity Discovery, Diagnostic, and Visualization	4
Parameter Estimation of Binned Hawkes Processes	4
Assessing and Visualizing Simultaneous Simulation Error	4
Scaled Torus Principal Component Analysis	4
Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation	4
Interactive Slice Visualization for Exploring Machine Learning Models	4
The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC	4
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	4
Dimension Reduction for Outlier Detection Using DOBIN	4
Scalable Hyperparameter Selection for Latent Dirichlet Allocation	4
Fast Markov Chain Monte Carlo for High-Dimensional Bayesian Regression Models With Shrinkage Priors	4
Reduced-Dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models	4
A Relabeling Approach to Handling the Class Imbalance Problem for Logistic Regression	4
The q–q Boxplot	4
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data	4
Improving Estimation in Functional Linear Regression With Points of Impact: Insights Into Google AdWords	4
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	4
A General Method for Deriving Tight Symbolic Bounds on Causal Effects	3
Predicting the Output From a Stochastic Computer Model When a Deterministic Approximation is Available	3
Directional Quantile Classifiers	3
More Powerful Selective Inference for the Graph Fused Lasso	3
Sampling Based Estimation of In-Degree Distribution for Directed Complex Networks	3
Adaptive Preferential Sampling in Phylodynamics With an Application to SARS-CoV-2	3
Partition-Based Nonstationary Covariance Estimation Using the Stochastic Score Approximation	3
Enforcing Stationarity through the Prior in Vector Autoregressions	3
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies	3
Visualization for Interval Data	3
Model-Based Edge Clustering	3
A User-Friendly Computational Framework for Robust Structured Regression with the L₂ Criterion	3
Sequential Learning of Regression Models by Penalized Estimation	3
Global Likelihood Sampler for Multimodal Distributions	3
Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines	3
Nonreversible Jump Algorithms for Bayesian Nested Model Selection	3
A Fast and Accurate Approximation to the Distributions of Quadratic Forms of Gaussian Variables	3
Maximum Likelihood Estimation and Graph Matching in Errorfully Observed Networks	3
An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model	3
Mixture of Linear Models Co-supervised by Deep Neural Networks	3
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings	3
Matrix Autoregressive Spatio-Temporal Models	3
A Tree-Based Semi-Varying Coefficient Model for the COM-Poisson Distribution	3
Probabilistic K -means with Local Alignment for Clustering and Motif Discovery in Functional Data	3
Burning Sage: Reversing the Curse of Dimensionality in the Visualization of High-Dimensional Data	3
Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models	3
Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes	3
Kriging Riemannian Data via Random Domain Decompositions	3
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks	3
Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty	3
Mutually Exciting Point Process Graphs for Modeling Dynamic Networks	3
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series	3
Approximating Partial Likelihood Estimators via Optimal Subsampling	3
Random Forest Adjustment for Approximate Bayesian Computation	3
Fast Forecast Reconciliation Using Linear Models	3