OOIR: Observatory of International Research

Papers

(The median citation count of Statistical Science is 1. 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
A General Framework for Vecchia Approximations of Gaussian Processes	91
The Box–Cox Transformation: Review and Extensions	68
Exponential-Family Models of Random Graphs: Inference in Finite, Super and Infinite Population Scenarios	54
A Selective Overview of Deep Learning	48
Revisiting the Gelman–Rubin Diagnostic	47
Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons	39
The Dependent Dirichlet Process and Related Models	32
Additive and Multiplicative Effects Network Models	30
In Defense of the Indefensible: A Very Naïve Approach to High-Dimensional Inference	27
The GENIUS Approach to Robust Mendelian Randomization Inference	24
Analyzing Stochastic Computer Models: A Review with Opportunities	21
Robust High-Dimensional Factor Models with Applications to Statistical Machine Learning	20
Convex Relaxation Methods for Community Detection	18
A Unified Primal Dual Active Set Algorithm for Nonconvex Sparse Recovery	18
Game-Theoretic Statistics and Safe Anytime-Valid Inference	17
Maximum Likelihood Multiple Imputation: Faster Imputations and Consistent Standard Errors Without Posterior Draws	16
Bipartite Causal Inference with Interference	15
Choosing Among Notions of Multivariate Depth Statistics	15
Testing Randomness Online	15
Sparse Regression: Scalable Algorithms and Empirical Performance	14
Stein’s Method Meets Computational Statistics: A Review of Some Recent Developments	13
Aitchison’s Compositional Data Analysis 40 Years on: A Reappraisal	13
Minimax Rates in Network Analysis: Graphon Estimation, Community Detection and Hypothesis Testing	13
Statistical Dependence: Beyond Pearson’s ρ	12
A General Framework for the Analysis of Adaptive Experiments	12

Judicious Judgment Meets Unsettling Updating: Dilation, Sure Loss and Simpson’s Paradox	12
Response-Adaptive Randomization in Clinical Trials: From Myths to Practical Considerations	11
Challenges in Markov Chain Monte Carlo for Bayesian Neural Networks	11
Symmetrical and Non-symmetrical Variants of Three-Way Correspondence Analysis for Ordered Variables	11
On Estimation and Inference in Latent Structure Random Graphs	10
A Horse Race between the Block Maxima Method and the Peak–over–Threshold Approach	10
Real-Time Estimation of COVID-19 Infections: Deconvolution and Sensor Fusion	10
A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and Likelihood Ratio	10
Statistical Modeling for Practical Pooled Testing During the COVID-19 Pandemic	9
Causal Inference Methods for Combining Randomized Trials and Observational Studies: A Review	8
Methods to Compute Prediction Intervals: A Review and New Results	7
Power Calculations for Replication Studies	7
A Look at Robustness and Stability of $\ell_{1}$-versus $\ell_{0}$-Regularization: Discussion of Papers by Bertsimas et al. and Hastie et al.	7
Modern Bayesian Experimental Design	7
On General Notions of Depth for Regression	7
Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality	6
Identification of Causal Effects Within Principal Strata Using Auxiliary Variables	6
30 Years of Synthetic Data	6
The SPDE Approach to Matérn Fields: Graph Representations	6
Statistical Challenges in Tracking the Evolution of SARS-CoV-2	6
Confidence as Likelihood	6
Gambler’s Ruin and the ICM	6
Principal Fairness for Human and Algorithmic Decision-Making	6
Confidence and Discoveries with E-values	5
Additive Bayesian Variable Selection under Censoring and Misspecification	5
Approximating Bayes in the 21st Century	5
The Covariate-Adjusted ROC Curve: The Concept and Its Importance, Review of Inferential Methods, and a New Bayesian Estimator	5
Rejoinder: Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons	5
Network Modeling in Biology: Statistical Methods for Gene and Brain Networks	5
Local scale invariance and robustness of proper scoring rules	5
Intention-to-Treat Comparisons in Randomized Trials	4
Past, Present and Future of Software for Bayesian Inference	4
Being a Public Health Statistician During a Global Pandemic	4
A Statistical Framework for Modern Network Science	4
Stochastic Approximation: From Statistical Origin to Big-Data, Multidisciplinary Applications	4
Seven Principles for Rapid-Response Data Science: Lessons Learned from Covid-19 Forecasting	3
The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning	3
Confidence Intervals for Seroprevalence	3
A Regression Perspective on Generalized Distance Covariance and the Hilbert–Schmidt Independence Criterion	3
Bayesian Analysis of Rank Data with Covariates and Heterogeneous Rankers	3
Online Multiple Hypothesis Testing	3
Replicability Across Multiple Studies	3
The Poisson Binomial Distribution— Old & New	3
High-Performance Statistical Computing in the Computing Environments of the 2020s	3
Statistical Aspects of the Quantum Supremacy Demonstration	3
Discussion of “Best Subset, Forward Stepwise or Lasso? Analysis and Recommendations Based on Extensive Comparisons”	3
Khinchin’s 1929 Paper on Von Mises’ Frequency Theory of Probability	2
Some Perspectives on Inference in High Dimensions	2
Computing Bayes: From Then ‘Til Now	2
Cross-Study Replicability in Cluster Analysis	2

A Discussion on Practical Considerations with Sparse Regression Methodologies	2
Distributed Bayesian Inference in Massive Spatial Data	2
Interpreting p-Values and Confidence Intervals Using Well-Calibrated Null Preference Priors	2
Comment: Settle the Unsettling: An Inferential Models Perspective	2
Diffusion Smoothing for Spatial Point Patterns	2
Comment: On Focusing, Soft and Strong Revision of Choquet Capacities and Their Role in Statistics	2
Data Science in a Time of Crisis: Lessons from the Pandemic	1
Variational Inference for Cutting Feedback in Misspecified Models	1
Bayesian Adaptive Randomization with Compound Utility Functions	1
Modeling the Occurrence of Events Subject to a Reporting Delay via an EM Algorithm	1
Comment: Response Adaptive Randomization in Practice	1
In Praise (and Search) of J. V. Uspensky	1
Modern Variable Selection in Action: Comment on the Papers by HTT and BPV	1
Comment: A Quarter Century of Methodological Research in Response-Adaptive Randomization	1
On Some Connections Between Esscher’s Tilting, Saddlepoint Approximations, and Optimal Transportation: A Statistical Perspective	1
Comment: Moving Beyond Sets of Probabilities	1
Experimental Design in Marketplaces	1
Can We Reliably Detect Biases that Matter in Observational Studies?	1
The Secret Life of I. J. Good	1
Rejoinder: Sparse Regression: Scalable Algorithms and Empirical Performance	1
A Hybrid Scan Gibbs Sampler for Bayesian Models with Latent Variables	1
A Conversation with Tze Leung Lai	1
Measurement Error Models: From Nonparametric Methods to Deep Neural Networks	1
Approximate Confidence Intervals for a Binomial p—Once Again	1
Distributionally Robust and Generalizable Inference	1
Replication Success Under Questionable Research Practices—a Simulation Study	1
Methods for Integrating Trials and Non-experimental Data to Examine Treatment Effect Heterogeneity	1
A Comparative Tour through the Simulation Algorithms for Max-Stable Processes	1
Studentization Versus Variance Stabilization: A Simple Way Out of an Old Dilemma	1