OOIR: Observatory of International Research

Papers

(The TQCC of Journal of the Royal Statistical Society Series B-Statistical Methodol 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 2021-12-01 to 2025-12-01.)

Article	Citations
Mark Pilling's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng	161
Authors’ reply to the Discussion of ‘From denoising diffusions to denoising Markov models’ at the Discussion Meeting on ‘Probabilistic and statistical aspects of machine learning’	73
Seconder of the vote of thanks to Evans and Didelez and contribution to the Discussion of ‘Parameterizing and simulating from causal models’	62
Catch me if you can: signal localization with knockoff e-values	54
Stefano Rizzelli’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen	52
Image response regression via deep neural networks	48
Maozai Tian, Keming Yu and Jiangfeng Wang’s contribution to the Discussion of ‘Safe testing’ by Grünwald, De Heide, and Koolen	45
Correlation adjusted debiased Lasso: debiasing the Lasso with inaccurate covariate model	42
On Functional Processes with Multiple Discontinuities	41
Strategic two-sample test via the two-armed bandit process	34
Safe testing	33
Yinqiu He, Yuqi Gu and Zhilian Ying's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng	31
Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods	30
Isadora Antoniano Villalobos's contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker	29
Computationally efficient and data-adaptive changepoint inference in high dimension	29
SymmPI: predictive inference for data with group symmetries	28
Corrected generalized cross-validation for finite ensembles of penalized estimators	28
Statistical testing under distributional shifts	27
Covariate adjustment in multiarmed, possibly factorial experiments	26
Synthetic Controls with Staggered Adoption	24
Proximal survival analysis to handle dependent right censoring	24
	24
Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis	24
Glenn Shafer’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen	23
Ying Zhou and Xinyi Zhang's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng	22

Ramses Mena Chavez's contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker	22
Rungang Han and Anru R. Zhangs contribution to the Discussion of ‘Vintage factor analysis with varimax performs statistical inference’ by Rohe & Zeng	21
Strong oracle guarantees for partial penalized tests of high-dimensional generalized linear models	21
Bootstrapping estimators based on the block maxima method	19
Proposer of the vote of thanks to Waudy-Smith and Ramdas and contribution to the Discussion of ‘Estimating means of bounded random variables by betting’	18
Estimating the efficiency gain of covariate-adjusted analyses in future clinical trials using external data	18
Pierre-Aurelien Gilliot, Christophe Andrieu, Anthony Lee, Song Liu, and Michael Whitehouse’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machi	17
Graphical criteria for the identification of marginal causal effects in continuous-time survival and event-history analyses	16
Authors’ reply to the Discussion of ‘Automatic change-point detection in time series via deep learning’ at the Discussion Meeting on ‘Probabilistic and statistical aspects of machine learning’	16
Robust model averaging prediction of longitudinal response with ultrahigh-dimensional covariates	16
Testing many constraints in possibly irregular models using incomplete U-statistics	16
A unified generalization of the inverse regression methods via column selection	16
Conformal prediction with local weights: randomization enables robust guarantees	15
Conformalized survival analysis	14
Randomisation inference beyond the sharp null: bounded null hypotheses and quantiles of individual treatment effects	14
Correction to: Semi-supervised approaches to efficient evaluation of model prediction performance	13
Spectral change point estimation for high-dimensional time series by sparse tensor decomposition	13
Andrej Srakar’s contribution to the Discussion of ‘Root and community inference on the latent growth process of a network’ by Crane and Xu	13
Broadcasted nonparametric tensor regression	13
Hernando Ombao’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’	13
Thomas S. Richardson’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes	13
Empirical Bayes PCA in High Dimensions	12
Bayesian Context Trees: Modelling and Exact Inference for Discrete Time Series	12
Engression: extrapolation through the lens of distributional regression	12
Orthogonalized moment aberration for mixed-level multi-stratum factorial designs with partially-relaxed orthogonal block structures	12
Estimating heterogeneous treatment effects with right-censored data via causal survival forests	11
Graph Based Gaussian Processes on Restricted Domains	11
Cluster extent inference revisited: quantification and localisation of brain activity	11
Seconder of the Vote of Thanks to Donget al.and Contribution to the Discussion of ‘Gaussian Differential Privacy’	11
Bertrand Clarke's contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker	10
J. Goseling and M.N.M. van Lieshout's Contribution to the Discussion of ‘Gaussian Differential Privacy’ by Donget al.	10
Tyler J. VanderWeele's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng	10
Kuldeep Kumar's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng	9
Authors’ Reply to the Discussion of ‘Gaussian Differential Privacy’ by Donget al.	9
A general framework for cutting feedback within modularized Bayesian inference	9
Scalable couplings for the random walk Metropolis algorithm	9
Ivor Cribben and Anastasiou Andreas’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’	9
Efficient Manifold Approximation with Spherelets	9
Anthony C Davison and Igor Rodionov’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas	9
Filippo Ascolani, Antonio Lijoi and Igor Prünster’s contribution to the Discussion of ‘Root and community inference on the latent growth process of a network’ by Crane and Xu	9
Root cause discovery via permutations and Cholesky decomposition	8
Zihao Wen and David L. Dowe’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen	8
Adaptive functional principal components analysis	8
Gradient synchronization for multivariate functional data, with application to brain connectivity	8
Ryan Martin’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas	8
Universal Prediction Band via Semi-Definite Programming	8
Conditional Independence Testing in Hilbert Spaces with Applications to Functional Data Analysis	8
Identification and estimation of causal peer effects using double negative controls for unmeasured network confounding	8
Martin Larsson and Johannes Ruf’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas	8
Oliver Hines and Karla Diaz-Ordazʼs Contribution to the Discussion of ‘Assumption-Lean Inference For Generalised Linear Model Parameters’ by Vansteelandt and Dukes	8

On the instrumental variable estimation with many weak and invalid instruments	8
Kuldeep Kumar’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes	7
Autoregressive optimal transport models	7
Issue Information	7
Marta Catalano, Augusto Fasano, Matteo Giordano, and Giovanni Rebaudo’s contribution to the Discussion of ‘Root and community inference on the latent growth process of a network’ by Crane and Xu	7
Seconder of the vote of thanks to Rohe & Zeng and contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’	7
Erratum: Usable and precise asymptotics for generalized linear mixed model analysis and design	7
Thorsten Dickhaus’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen	7
Yongmiao Hong, Oliver Linton, Jiajing Sun, and Meiting Zhu’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’	7
Goodness-of-fit tests for high-dimensional Gaussian graphical models via exchangeable sampling	7
Least squares for cardinal paired comparisons data	7
Yudong Chen and Yining Chen’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’	7
α-separability and adjustable combination of amplitude and phase model for functional data	6
Model-assisted sensitivity analysis for treatment effects under unmeasured confounding via regularized calibrated estimation	6
Convexity and measures of statistical association	6
Normalised latent measure factor models	6
Correction to: Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods	6
Semiparametric localized principal stratification analysis with continuous strata	6
Correction to: Holdout predictive checks for Bayesian model criticism	5
Graphical methods for Order-of-Addition experiments	5
Estimating means of bounded random variables by betting	5
Andrej Srakar’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen	5
Proposers of the vote of thanks to Crane and Xu and contribution to the Discussion of ‘Root and community inference on the latent growth process of a network’	5
Derandomised knockoffs: leveraging e-values for false discovery rate control	5
CovNet: Covariance Networks for Functional Data on Multidimensional Domains	5
Multi-resolution subsampling for linear classification with massive data	5
Ordering factorial experiments	5
Priyantha Wijayatunga’s contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes, and Walker	5
Ensemble methods for testing a global null	5
Peng Ding’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes	5
Semi-parametric tensor factor analysis by iteratively projected singular value decomposition	5
Correction to: Ordering factorial experiments	5
Analytic natural gradient updates for Cholesky factor in Gaussian variational approximation	5
Debiased inference for a covariate-adjusted regression function	4
Sparse Kronecker product decomposition: a general framework of signal region detection in image regression	4
Trace-class Gaussian priors for Bayesian learning of neural networks with MCMC	4
Spherical random projection	4
A fast asynchronous Markov chain Monte Carlo sampler for sparse Bayesian inference	4
Non-parametric inference about mean functionals of non-ignorable non-response data without identifying the joint distribution	4
Niwen Zhou and Xu Guo’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes	4
Stratification pattern enumerator and its applications	4
Interpretable discriminant analysis for functional data supported on random nonlinear domains with an application to Alzheimer’s disease	4
Jiaqi Gu and Guosheng Yin’s contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker	4
Yunxiao Chen and Gongjun Xu's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng	4
Yang Liu's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng	4
Martin Larsson, Aaditya Ramdas, and Johannes Ruf’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen	4
Testing high-dimensional multinomials with applications to text analysis	4
Randomized empirical likelihood test for ultra-high dimensional means under general covariances	4
Contents of Volume 84, 2022	4
Shakeel Gavioli-Akilagun’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’	4
Testing homogeneity: the trouble with sparse functional data	4
Steven R Howard's contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas	4
The Sceptical Bayes Factor for the Assessment of Replication Success	4
Policy evaluation for temporal and/or spatial dependent experiments	4