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 2020-03-01 to 2024-03-01.)

Article	Citations
Trimmed Constrained Mixed Effects Models: Formulations and Algorithms	46
Automated Redistricting Simulation Using Markov Chain Monte Carlo	34
Local Linear Forests	26
Anomaly Detection in High-Dimensional Data	25
Building Representative Matched Samples With Multi-Valued Treatments in Large Observational Studies	24
The Automatic Construction of Bootstrap Confidence Intervals	24
The Chi-Square Test of Distance Correlation	21
LowCon: A Design-based Subsampling Approach in a Misspecified Linear Model	21
Efficient Sampling and Structure Learning of Bayesian Networks	20
Survival Regression with Accelerated Failure Time Model in XGBoost	19
Model Interpretation Through Lower-Dimensional Posterior Summarization	17
Forward Event-Chain Monte Carlo: Fast Sampling by Randomness Control in Irreversible Markov Chains	16
Least-Square Approximation for a Distributed System	15
Search Algorithms and Loss Functions for Bayesian Clustering	14
Optimal Sampling for Generalized Linear Models Under Measurement Constraints	14
Data Integration with Oracle Use of External Information from Heterogeneous Populations	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
Robust Approximate Bayesian Inference With Synthetic Likelihood	13
Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering	13
High-Dimensional Copula Variational Approximation Through Transformation	13
Learning Multiple Quantiles With Neural Networks	12
Mixtures of Matrix-Variate Contaminated Normal Distributions	12
Nonlinear Variable Selection via Deep Neural Networks	12

Fast Univariate Inference for Longitudinal Functional Models	11
Fast Cross-validation for Multi-penalty High-dimensional Ridge Regression	11
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models	11
Predictive Distribution Modeling Using Transformation Forests	11
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
Bayesian Optimization Via Barrier Functions	10
Rapid Bayesian Inference for Expensive Stochastic Models	10
Randomized Spectral Clustering in Large-Scale Stochastic Block Models	10
Subset Multivariate Collective and Point Anomaly Detection	9
Latent Network Estimation and Variable Selection for Compositional Data Via Variational EM	9
Change-Point Detection for Graphical Models in the Presence of Missing Values	9
Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms	9
Co-Clustering of Ordinal Data via Latent Continuous Random Variables and Not Missing at Random Entries	9
Rerandomization Strategies for Balancing Covariates Using Pre-Experimental Longitudinal Data	9
Global Consensus Monte Carlo	9
Vecchia-Approximated Deep Gaussian Processes for Computer Experiments	8
Fast and Separable Estimation in High-Dimensional Tensor Gaussian Graphical Models	8
Multi-Resolution Filters for Massive Spatio-Temporal Data	8
d-blink: Distributed End-to-End Bayesian Entity Resolution	8
Smoothing Splines Approximation Using Hilbert Curve Basis Selection	8
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	8
Bayesian Variable Selection for Gaussian Copula Regression Models	8
Dependent Modeling of Temporal Sequences of Random Partitions	7
Model Checking for Hidden Markov Models	7
Efficient Bayesian Synthetic Likelihood With Whitening Transformations	7
Adaptive Bayesian SLOPE: Model Selection With Incomplete Data	7
Automatic Transformation and Integration to Improve Visualization and Discovery of Latent Effects in Imaging Data	7
Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks	7
Scalable Algorithms for Large Competing Risks Data	7
Multiple Imputation Through XGBoost	6
A Slice Tour for Finding Hollowness in High-Dimensional Data	6
Consensus Monte Carlo for Random Subsets Using Shared Anchors	6
Eigenvectors from Eigenvalues Sparse Principal Component Analysis	6
Importance Sampling with the Integrated Nested Laplace Approximation	6
Identifying Heterogeneous Effect Using Latent Supervised Clustering With Adaptive Fusion	6
Penalized Quantile Regression for Distributed Big Data Using the Slack Variable Representation	6
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation	6
Distributed Bayesian Inference in Linear Mixed-Effects Models	6
Marginally Calibrated Deep Distributional Regression	6
TheG-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models	6
Fast Computation of Latent Correlations	6
Model-Based Microbiome Data Ordination: A Variational Approximation Approach	6
Logistic Regression Models for Aggregated Data	6
Nonstationary Modeling With Sparsity for Spatial Data via the Basis Graphical Lasso	6
MIP-BOOST: Efficient and Effective L₀ Feature Selection for Linear Regression	6
Deep Learning With Functional Inputs	5
Clustering and Prediction With Variable Dimension Covariates	5
Cluster Optimized Proximity Scaling	5
Likelihood Evaluation of Jump-Diffusion Models Using Deterministic Nonlinear Filters	5

MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes	5
Nonparametric Anomaly Detection on Time Series of Graphs	5
Generalized Tensor Decomposition With Features on Multiple Modes	5
Bayesian Spatial Clustering of Extremal Behavior for Hydrological Variables	5
A Projection Pursuit Forest Algorithm for Supervised Classification	5
Sequential Learning of Active Subspaces	5
Testing for Equivalence of Network Distribution Using Subgraph Counts	5
Reproducible Hyperparameter Optimization	5
Generalized Link-Based Additive Survival Models with Informative Censoring	5
Online Updating of Survival Analysis	5
Delayed Acceptance ABC-SMC	5
Illumination Depth	5
A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data	5
Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance	5
Integrated Depths for Partially Observed Functional Data	5
Shrinking the Covariance Matrix Using Convex Penalties on the Matrix-Log Transformation	5
Two-Dimensional Functional Principal Component Analysis for Image Feature Extraction	4
Monte Carlo Simulation on the Stiefel Manifold via Polar Expansion	4
Markov Chain Importance Sampling—A Highly Efficient Estimator for MCMC	4
Interactive Slice Visualization for Exploring Machine Learning Models	4
Manifold Optimization-Assisted Gaussian Variational Approximation	4
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	4
Bayesian Variational Inference for Exponential Random Graph Models	4
Assessing and Visualizing Simultaneous Simulation Error	4
Estimating Multiple Precision Matrices With Cluster Fusion Regularization	4
Nonlinear Functional Modeling Using Neural Networks	4
Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation	4
Modeling Nonstationary Extreme Dependence With Stationary Max-Stable Processes and Multidimensional Scaling	4
Poisson Kernel-Based Clustering on the Sphere: Convergence Properties, Identifiability, and a Method of Sampling	4
Dimension Reduction for Outlier Detection Using DOBIN	4
Generalized Spatially Varying Coefficient Models	4
Scalable Hyperparameter Selection for Latent Dirichlet Allocation	4
Scaled Torus Principal Component Analysis	4
Fast Markov Chain Monte Carlo for High-Dimensional Bayesian Regression Models With Shrinkage Priors	4
A Relabeling Approach to Handling the Class Imbalance Problem for Logistic Regression	4
The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC	4
Scalable Computation of Predictive Probabilities in Probit Models with Gaussian Process Priors	4
MCVIS: A New Framework for Collinearity Discovery, Diagnostic, and Visualization	4
Zig-Zag Sampling for Discrete Structures and Nonreversible Phylogenetic MCMC	4
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference	4
Probabilistic K -means with Local Alignment for Clustering and Motif Discovery in Functional Data	3
A General Method for Deriving Tight Symbolic Bounds on Causal Effects	3
Kriging Riemannian Data via Random Domain Decompositions	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
Enforcing Stationarity through the Prior in Vector Autoregressions	3
Random Forest Adjustment for Approximate Bayesian Computation	3
Visualization for Interval Data	3
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	3
Burning Sage: Reversing the Curse of Dimensionality in the Visualization of High-Dimensional Data	3
A User-Friendly Computational Framework for Robust Structured Regression with the L₂ Criterion	3
Global Likelihood Sampler for Multimodal Distributions	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
Nonreversible Jump Algorithms for Bayesian Nested Model Selection	3
Mixture of Linear Models Co-supervised by Deep Neural Networks	3
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	3
Implicit Copula Variational Inference	3
Model-Based Edge Clustering	3
Parameter Estimation of Binned Hawkes Processes	3
Predicting the Output From a Stochastic Computer Model When a Deterministic Approximation is Available	3
Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models	3
Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines	3
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks	3
Reduced-Dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models	3
Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty	3
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series	3
Matrix Autoregressive Spatio-Temporal Models	3
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data	3
Forward Stepwise Deep Autoencoder-Based Monotone Nonlinear Dimensionality Reduction Methods	3
Sequential Learning of Regression Models by Penalized Estimation	3