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 2020-08-01 to 2024-08-01.)

Article	Citations
Trimmed Constrained Mixed Effects Models: Formulations and Algorithms	65
Local Linear Forests	36
Anomaly Detection in High-Dimensional Data	28
Survival Regression with Accelerated Failure Time Model in XGBoost	26
The Chi-Square Test of Distance Correlation	25
Efficient Sampling and Structure Learning of Bayesian Networks	25
LowCon: A Design-based Subsampling Approach in a Misspecified Linear Model	23
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models	22
Least-Square Approximation for a Distributed System	21
Model Interpretation Through Lower-Dimensional Posterior Summarization	21
Search Algorithms and Loss Functions for Bayesian Clustering	20
Data Integration with Oracle Use of External Information from Heterogeneous Populations	19
Robust Approximate Bayesian Inference With Synthetic Likelihood	18
Learning Multiple Quantiles With Neural Networks	17
Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods	16
Fast Univariate Inference for Longitudinal Functional Models	15
Predictive Distribution Modeling Using Transformation Forests	15
Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and Its Variance Estimate	14
Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering	14
Additive Functional Cox Model	14
Fast Cross-validation for Multi-penalty High-dimensional Ridge Regression	14
Randomized Spectral Clustering in Large-Scale Stochastic Block Models	13
Bayesian Optimization Via Barrier Functions	13
Mixtures of Matrix-Variate Contaminated Normal Distributions	13
Rapid Bayesian Inference for Expensive Stochastic Models	12

Nonlinear Variable Selection via Deep Neural Networks	12
Multi-Resolution Filters for Massive Spatio-Temporal Data	11
A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data	11
The Holdout Randomization Test for Feature Selection in Black Box Models	11
Latent Network Estimation and Variable Selection for Compositional Data Via Variational EM	11
Asymptotically Exact Data Augmentation: Models, Properties, and Algorithms	10
d-blink: Distributed End-to-End Bayesian Entity Resolution	10
Subset Multivariate Collective and Point Anomaly Detection	10
Fast Computation of Latent Correlations	10
Vecchia-Approximated Deep Gaussian Processes for Computer Experiments	10
Fast and Separable Estimation in High-Dimensional Tensor Gaussian Graphical Models	10
Smoothing Splines Approximation Using Hilbert Curve Basis Selection	9
Eigenvectors from Eigenvalues Sparse Principal Component Analysis	9
Global Consensus Monte Carlo	9
Adaptive Bayesian SLOPE: Model Selection With Incomplete Data	9
Bayesian Variable Selection for Gaussian Copula Regression Models	9
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	9
Change-Point Detection for Graphical Models in the Presence of Missing Values	9
Nonlinear Functional Modeling Using Neural Networks	8
Likelihood Evaluation of Jump-Diffusion Models Using Deterministic Nonlinear Filters	8
Multiple Imputation Through XGBoost	8
Deep Learning With Functional Inputs	8
Efficient Bayesian Synthetic Likelihood With Whitening Transformations	8
Sequential Learning of Active Subspaces	8
Online Updating of Survival Analysis	8
Two-Dimensional Functional Principal Component Analysis for Image Feature Extraction	8
Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks	8
Scalable Algorithms for Large Competing Risks Data	8
Clustering and Prediction With Variable Dimension Covariates	7
Dependent Modeling of Temporal Sequences of Random Partitions	7
TheG-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models	7
An Optimal Transport Approach for Selecting a Representative Subsample with Application in Efficient Kernel Density Estimation	7
Logistic Regression Models for Aggregated Data	7
Nonparametric Anomaly Detection on Time Series of Graphs	7
Monte Carlo Simulation on the Stiefel Manifold via Polar Expansion	7
MIP-BOOST: Efficient and Effective L₀ Feature Selection for Linear Regression	7
Model-Based Microbiome Data Ordination: A Variational Approximation Approach	7
Generalized Tensor Decomposition With Features on Multiple Modes	7
Marginally Calibrated Deep Distributional Regression	7
Cluster Optimized Proximity Scaling	7
Shrinkage Bayesian Causal Forests for Heterogeneous Treatment Effects Estimation	7
Integrated Depths for Partially Observed Functional Data	7
Distributed Bayesian Inference in Linear Mixed-Effects Models	7
The q–q Boxplot	6
MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes	6
Importance Sampling with the Integrated Nested Laplace Approximation	6
Penalized Quantile Regression for Distributed Big Data Using the Slack Variable Representation	6
Nonstationary Modeling With Sparsity for Spatial Data via the Basis Graphical Lasso	6
Transfer Learning of Individualized Treatment Rules from Experimental to Real-World Data	6
Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference	5

Shrinking the Covariance Matrix Using Convex Penalties on the Matrix-Log Transformation	5
Design Principles for Data Analysis	5
A Relabeling Approach to Handling the Class Imbalance Problem for Logistic Regression	5
Manifold Optimization-Assisted Gaussian Variational Approximation	5
Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference	5
Zig-Zag Sampling for Discrete Structures and Nonreversible Phylogenetic MCMC	5
Sequential Learning of Regression Models by Penalized Estimation	5
Estimating Multiple Precision Matrices With Cluster Fusion Regularization	5
A General Method for Deriving Tight Symbolic Bounds on Causal Effects	5
Spectrally Sparse Nonparametric Regression via Elastic Net Regularized Smoothers	5
Interactive Slice Visualization for Exploring Machine Learning Models	5
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	5
Dimension Reduction for Outlier Detection Using DOBIN	5
Reproducible Hyperparameter Optimization	5
Parameter Estimation of Binned Hawkes Processes	5
Interval Censored Recursive Forests	5
A Projection Pursuit Forest Algorithm for Supervised Classification	5
Nonreversible Jump Algorithms for Bayesian Nested Model Selection	5
An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model	5
Scalable Computation of Predictive Probabilities in Probit Models with Gaussian Process Priors	5
Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance	5
Forward Stepwise Deep Autoencoder-Based Monotone Nonlinear Dimensionality Reduction Methods	5
Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives	4
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	4
Fast Markov Chain Monte Carlo for High-Dimensional Bayesian Regression Models With Shrinkage Priors	4
Markov Chain Importance Sampling—A Highly Efficient Estimator for MCMC	4
The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC	4
Enforcing Stationarity through the Prior in Vector Autoregressions	4
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies	4
Assessing and Visualizing Simultaneous Simulation Error	4
Scaled Torus Principal Component Analysis	4
Variational Bayes in State Space Models: Inferential and Predictive Accuracy	4
Modeling Nonstationary Extreme Dependence With Stationary Max-Stable Processes and Multidimensional Scaling	4
More Powerful Selective Inference for the Graph Fused Lasso	4
Model-Based Edge Clustering	4
Matrix Autoregressive Spatio-Temporal Models	4
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model	4
A User-Friendly Computational Framework for Robust Structured Regression with the L₂ Criterion	4
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks	4
Reduced-Dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models	4
Practical Network Modeling via Tapered Exponential-Family Random Graph Models	4
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	4
Features of the Polynomial Biplot for Ordered Contingency Tables	3
Popularity Adjusted Block Models are Generalized Random Dot Product Graphs	3
Analysis of Professional Basketball Field Goal Attempts via a Bayesian Matrix Clustering Approach	3
Visualization for Interval Data	3
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates	3
Approximating Partial Likelihood Estimators via Optimal Subsampling	3
Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines	3
Fast Forecast Reconciliation Using Linear Models	3
Comparing Two Samples Through Stochastic Dominance: A Graphical Approach	3
Semi-Complete Data Augmentation for Efficient State Space Model Fitting	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
Accelerated and Interpretable Oblique Random Survival Forests	3
Low-rank, Orthogonally Decomposable Tensor Regression With Application to Visual Stimulus Decoding of fMRI Data	3
Silhouettes and Quasi Residual Plots for Neural Nets and Tree-based Classifiers	3
Mixture of Linear Models Co-supervised by Deep Neural Networks	3
clusterMLD: An Efficient Hierarchical Clustering Method for Multivariate Longitudinal Data	3
Random Forest Adjustment for Approximate Bayesian Computation	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
Spectral Clustering via Adaptive Layer Aggregation for Multi-Layer Networks	3
Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model	3
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator	3
Adaptive Preferential Sampling in Phylodynamics With an Application to SARS-CoV-2	3
Sampling Based Estimation of In-Degree Distribution for Directed Complex Networks	3
Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions	3
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series	3
Partition-Based Nonstationary Covariance Estimation Using the Stochastic Score Approximation	3
Mutually Exciting Point Process Graphs for Modeling Dynamic Networks	3
Global Likelihood Sampler for Multimodal Distributions	3
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings	3
Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models	3
Selective Imputation of Covariates in High Dimensional Censored Data	3
Directional Quantile Classifiers	3
Locally Sparse Function-on-Function Regression	3
Kriging Riemannian Data via Random Domain Decompositions	3
Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes	3
Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty	3