OOIR: Observatory of International Research

Papers

(The TQCC of Biometrika is 4. 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
Heterogeneity-aware and communication-efficient distributed statistical inference	34
Mean decrease accuracy for random forests: inconsistency, and a practical solution via the Sobol-MDA	32
On the power of Chatterjee’s rank correlation	24
Inference on the average treatment effect under minimization and other covariate-adaptive randomization methods	19
Regression adjustment in completely randomized experiments with a diverging number of covariates	17
Consistency guarantees for greedy permutation-based causal inference algorithms	16
Componentwise approximate Bayesian computation via Gibbs-like steps	15
Partial separability and functional graphical models for multivariate Gaussian processes	15
Fast and powerful conditional randomization testing via distillation	15
Searching for robust associations with a multi-environment knockoff filter	15
On boosting the power of Chatterjee’s rank correlation	14
Propensity scores in the design of observational studies for causal effects	14
Valid sequential inference on probability forecast performance	14
Dependent censoring based on parametric copulas	14
Seeded binary segmentation: a general methodology for fast and optimal changepoint detection	13
A minimum aberration-type criterion for selecting space-filling designs	12
Fréchet sufficient dimension reduction for random objects	12
Graphical Gaussian process models for highly multivariate spatial data	11
Maximum likelihood estimation for semiparametric regression models with panel count data	11
Distribution-on-distribution regression via optimal transport maps	11
Sparse functional linear discriminant analysis	11
Confidence regions in Wasserstein distributionally robust estimation	11
Data integration: exploiting ratios of parameter estimates from a reduced external model	11
Joint latent space models for network data with high-dimensional node variables	10
Lasso-adjusted treatment effect estimation under covariate-adaptive randomization	10

Clustering consistency with Dirichlet process mixtures	10
Generalized infinite factorization models	9
High-dimensional semi-supervised learning: in search of optimal inference of the mean	9
On the implied weights of linear regression for causal inference	9
Splitting strategies for post-selection inference	9
Robust differential abundance test in compositional data	8
On semiparametric modelling, estimation and inference for survival data subject to dependent censoring	8
Statistical inference for streamed longitudinal data	8
Efficient semiparametric estimation of network treatment effects under partial interference	8
Elicitation complexity of statistical properties	7
Scalable and accurate variational Bayes for high-dimensional binary regression models	7
Average direct and indirect causal effects under interference	7
More for less: predicting and maximizing genomic variant discovery via Bayesian nonparametrics	7
Minimax designs for causal effects in temporal experiments with treatment habituation	7
Adjusting the Benjamini–Hochberg method for controlling the false discovery rate in knockoff-assisted variable selection	7
Regression-based causal inference with factorial experiments: estimands, model specifications and design-based properties	7
Risk bounds for quantile trend filtering	7
A proximal distance algorithm for likelihood-based sparse covariance estimation	6
A high-dimensional power analysis of the conditional randomization test and knockoffs	6
Functional linear regression for discretely observed data: from ideal to reality	6
Lugsail lag windows for estimating time-average covariance matrices	6
Estimation of the cure rate for distributions in the Gumbel maximum domain of attraction under insufficient follow-up	6
Scalar-on-function local linear regression and beyond	6
Inverse moment methods for sufficient forecasting using high-dimensional predictors	6
A discrete bouncy particle sampler	6
High-dimensional log-error-in-variable regression with applications to microbial compositional data analysis	6
Gaussian universal likelihood ratio testing	6
Honest calibration assessment for binary outcome predictions	6
Localized conformal prediction: a generalized inference framework for conformal prediction	5
Linearized maximum rank correlation estimation	5
Heterogeneous coefficients, control variables and identification of multiple treatment effects	5
An approximate randomization test for the high-dimensional two-sample Behrens–Fisher problem under arbitrary covariances	5
Latent space models for multiplex networks with shared structure	5
Learning block structures in U-statistic-based matrices	5
On the inconsistency of matching without replacement	5
Semi-exact control functionals from Sard’s method	5
Multi-scale Fisher’s independence test for multivariate dependence	5
Identifiability of causal effects with multiple causes and a binary outcome	5
A generalized Bayes framework for probabilistic clustering	5
Spectral adjustment for spatial confounding	5
Optimal post-selection inference for sparse signals: a nonparametric empirical Bayes approach	4
Interpoint-ranking sign covariance for the test of independence	4
Semiparametric counterfactual density estimation	4
Soft calibration for selection bias problems under mixed-effects models	4
Estimation under matrix quadratic loss and matrix superharmonicity	4
Dimension reduction for covariates in network data	4
Deep Kronecker network	4
Nontestability of instrument validity under continuous treatments	4
Additive models for symmetric positive-definite matrices and Lie groups	4
A simple and general debiased machine learning theorem with finite-sample guarantees	4

Online inference with debiased stochastic gradient descent	4
Estimation of genetic correlation with summary association statistics	4
No-harm calibration for generalized Oaxaca–Blinder estimators	4
Estimation of local treatment effects under the binary instrumental variable model	4
Thresholded graphical lasso adjusts for latent variables	4
Gradient-based sparse principal component analysis with extensions to online learning	4
E-values as unnormalized weights in multiple testing	4
Targeted optimal treatment regime learning using summary statistics	4
Functional hybrid factor regression model for handling heterogeneity in imaging studies	4
A subsampling perspective for extending the validity of state-of-the-art bootstraps in the frequency domain	4
Design-based theory for cluster rerandomization	4
Populations of unlabelled networks: graph space geometry and generalized geodesic principal components	4