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 2020-11-01 to 2024-11-01.)

Article	Citations
Trimmed Constrained Mixed Effects Models: Formulations and Algorithms	67
Local Linear Forests	38
Visualizing Variable Importance and Variable Interaction Effects in Machine Learning Models	29
Survival Regression with Accelerated Failure Time Model in XGBoost	28
Efficient Sampling and Structure Learning of Bayesian Networks	25
The Chi-Square Test of Distance Correlation	25
Least-Square Approximation for a Distributed System	24
LowCon: A Design-based Subsampling Approach in a Misspecified Linear Model	23
Variable Selection with Multiply-Imputed Datasets: Choosing Between Stacked and Grouped Methods	21
Search Algorithms and Loss Functions for Bayesian Clustering	21
Data Integration with Oracle Use of External Information from Heterogeneous Populations	20
Robust Approximate Bayesian Inference With Synthetic Likelihood	19
Fast Univariate Inference for Longitudinal Functional Models	17
Learning Multiple Quantiles With Neural Networks	17
Additive Functional Cox Model	16
Latent Network Estimation and Variable Selection for Compositional Data Via Variational EM	15
Predictive Distribution Modeling Using Transformation Forests	15
Fast Cross-validation for Multi-penalty High-dimensional Ridge Regression	14
Bayesian Optimization Via Barrier Functions	14
Mixtures of Matrix-Variate Contaminated Normal Distributions	13
Randomized Spectral Clustering in Large-Scale Stochastic Block Models	13
Rapid Bayesian Inference for Expensive Stochastic Models	12
A Pseudo-Likelihood Approach to Linear Regression With Partially Shuffled Data	12
Nonlinear Functional Modeling Using Neural Networks	11
On Moments of Folded and Doubly Truncated Multivariate Extended Skew-Normal Distributions	11

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

Modeling Nonstationary Extreme Dependence With Stationary Max-Stable Processes and Multidimensional Scaling	5
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks	5
Nonreversible Jump Algorithms for Bayesian Nested Model Selection	5
Analysis of Professional Basketball Field Goal Attempts via a Bayesian Matrix Clustering Approach	5
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo	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
Parameter Estimation of Binned Hawkes Processes	5
Design Principles for Data Analysis	5
A Relabeling Approach to Handling the Class Imbalance Problem for Logistic Regression	5
Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model	5
An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model	5
Matrix Autoregressive Spatio-Temporal Models	5
Forward Stepwise Deep Autoencoder-Based Monotone Nonlinear Dimensionality Reduction Methods	5
Reproducible Hyperparameter Optimization	5
Estimating Multiple Precision Matrices With Cluster Fusion Regularization	5
Interactive Slice Visualization for Exploring Machine Learning Models	5
Markov Chain Importance Sampling—A Highly Efficient Estimator for MCMC	5
A Unified Algorithm for Penalized Convolution Smoothed Quantile Regression	5
Approximating Partial Likelihood Estimators via Optimal Subsampling	5
Generalized Connectivity Matrix Response Regression with Applications in Brain Connectivity Studies	5
Accelerated and Interpretable Oblique Random Survival Forests	4
Practical Network Modeling via Tapered Exponential-Family Random Graph Models	4
Enforcing Stationarity through the Prior in Vector Autoregressions	4
Beyond Linear Dynamic Functional Connectivity: A Vine Copula Change Point Model	4
Scaled Torus Principal Component Analysis	4
Global Likelihood Sampler for Multimodal Distributions	4
Features of the Polynomial Biplot for Ordered Contingency Tables	4
Variational Bayes in State Space Models: Inferential and Predictive Accuracy	4
The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC	4
Low-rank, Orthogonally Decomposable Tensor Regression With Application to Visual Stimulus Decoding of fMRI Data	4
Dimension Reduction Forests: Local Variable Importance Using Structured Random Forests	4
Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	4
Probabilistic K -means with Local Alignment for Clustering and Motif Discovery in Functional Data	4
Spectral Clustering via Adaptive Layer Aggregation for Multi-Layer Networks	4
Adaptive Preferential Sampling in Phylodynamics With an Application to SARS-CoV-2	4
Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty	4
More Powerful Selective Inference for the Graph Fused Lasso	4
Partition-Based Nonstationary Covariance Estimation Using the Stochastic Score Approximation	4
Joint Modeling of Longitudinal Imaging and Survival Data	4
A User-Friendly Computational Framework for Robust Structured Regression with the L₂ Criterion	4
Fast Markov Chain Monte Carlo for High-Dimensional Bayesian Regression Models With Shrinkage Priors	4
Sampling Based Estimation of In-Degree Distribution for Directed Complex Networks	4
Locally Sparse Function-on-Function Regression	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
Silhouettes and Quasi Residual Plots for Neural Nets and Tree-based Classifiers	3
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series	3
Random Forest Adjustment for Approximate Bayesian Computation	3
A Quantum Parallel Markov Chain Monte Carlo	3
Fast Forecast Reconciliation Using Linear Models	3
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates	3
Bayesian Model Selection in Additive Partial Linear Models Via Locally Adaptive Splines	3
Link Prediction for Egocentrically Sampled Networks	3
Statistical Analysis of Fixed Mini-Batch Gradient Descent Estimator	3
Comparing Two Samples Through Stochastic Dominance: A Graphical Approach	3
A Simple Algorithm for Exact Multinomial Tests	3
Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions	3
A Bayesian Singular Value Decomposition Procedure for Missing Data Imputation	3
Mutually Exciting Point Process Graphs for Modeling Dynamic Networks	3
Model Based Screening Embedded Bayesian Variable Selection for Ultra-high Dimensional Settings	3
clusterMLD: An Efficient Hierarchical Clustering Method for Multivariate Longitudinal 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
Efficient Approximation of Gromov-Wasserstein Distance Using Importance Sparsification	3
Directional Quantile Classifiers	3
Semi-Complete Data Augmentation for Efficient State Space Model Fitting	3
Kriging Riemannian Data via Random Domain Decompositions	3
Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes	3
Popularity Adjusted Block Models are Generalized Random Dot Product Graphs	3
Mixture of Linear Models Co-supervised by Deep Neural Networks	3
Visualization for Interval Data	3
Regularized Linear Programming Discriminant Rule with Folded Concave Penalty for Ultrahigh-Dimensional Data	3
Efficient Posterior Sampling for Bayesian Poisson Regression	3
Selective Imputation of Covariates in High Dimensional Censored Data	3
Functional Additive Models on Manifolds of Planar Shapes and Forms	3
A Nearest Neighbor Open-Set Classifier based on Excesses of Distance Ratios	3
DeepMoM: Robust Deep Learning With Median-of-Means	3