Journal of the Royal Statistical Society Series B-Statistical Methodol

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 2022-06-01 to 2026-06-01.)
ArticleCitations
Mark Pilling's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng80
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’63
Seconder of the vote of thanks to Evans and Didelez and contribution to the Discussion of ‘Parameterizing and simulating from causal models’61
Stefano Rizzelli’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen60
Maozai Tian, Keming Yu and Jiangfeng Wang’s contribution to the Discussion of ‘Safe testing’ by Grünwald, De Heide, and Koolen46
Strategic two-sample test via the two-armed bandit process44
Correlation adjusted debiased Lasso: debiasing the Lasso with inaccurate covariate model36
Skew-symmetric approximations of posterior distributions34
Catch me if you can: signal localization with knockoff e-values34
Statistical inference for Gaussian Whittle–Matérn fields on metric graphs33
Image response regression via deep neural networks31
Zihao Wen and David L. Dowe’s contribution to the Discussion of ‘Statistical exploration of the manifold hypothesis’ by Whiteley et al.30
Safaa K. Kadhem’s contribution to the Discussion on ‘Statistical exploration of the manifold hypothesis’ by Nick Whiteley, Annie Grayb, and Patrick Rubin-Delanchy30
Safe testing29
Yinqiu He, Yuqi Gu and Zhilian Ying's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng26
Isadora Antoniano Villalobos's contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker24
Proposer of the vote of thanks to Whiteley et al. and contribution to the Discussion of ‘Statistical exploration of the Manifold Hypothesis’23
Scalability of Metropolis-within-Gibbs schemes for high-dimensional Bayesian models19
Using a two-parameter sensitivity analysis framework to efficiently combine randomized and nonrandomized studies19
Corrected generalized cross-validation for finite ensembles of penalized estimators19
Pitman efficiency lower bounds for multivariate distribution-free tests based on optimal transport18
Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods18
Computationally efficient and data-adaptive changepoint inference in high dimension18
Statistical testing under distributional shifts18
SymmPI: predictive inference for data with group symmetries18
Oracle arrays and their use for constructing space-filling designs17
Covariate adjustment in multiarmed, possibly factorial experiments17
16
Proximal survival analysis to handle dependent right censoring16
Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis16
Anytime validity is free: inducing sequential tests16
Ramses Mena Chavez's contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker15
Glenn Shafer’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen15
Ying Zhou and Xinyi Zhang's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng14
Strong oracle guarantees for partial penalized tests of high-dimensional generalized linear models13
Robust model averaging prediction of longitudinal response with ultrahigh-dimensional covariates13
Rungang Han and Anru R. Zhangs contribution to the Discussion of ‘Vintage factor analysis with varimax performs statistical inference’ by Rohe & Zeng13
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’12
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 machi12
Graphical criteria for the identification of marginal causal effects in continuous-time survival and event-history analyses12
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’12
Conformal prediction with local weights: randomization enables robust guarantees11
Estimating the efficiency gain of covariate-adjusted analyses in future clinical trials using external data11
Testing many constraints in possibly irregular models using incomplete U-statistics11
Tian, Liu and Tan's contribution to the Discussion of ‘Augmented balancing weights as linear regression’ by Bruns-Smith et al11
Bootstrapping estimators based on the block maxima method11
Randomisation inference beyond the sharp null: bounded null hypotheses and quantiles of individual treatment effects11
Seconder of the vote of thanks to Bruns-Smith et al. and contribution to the Discussion of ‘Augmented balancing weights as linear regression'10
Hernando Ombao’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’10
A unified generalization of the inverse regression methods via column selection10
Cluster extent inference revisited: quantification and localisation of brain activity10
Thomas S. Richardson’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes10
Andrej Srakar’s contribution to the Discussion of ‘Root and community inference on the latent growth process of a network’ by Crane and Xu10
Conformalized survival analysis10
Broadcasted nonparametric tensor regression9
Engression: extrapolation through the lens of distributional regression9
Correction to: Semi-supervised approaches to efficient evaluation of model prediction performance9
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 Xu9
Spectral change point estimation for high-dimensional time series by sparse tensor decomposition9
Estimating heterogeneous treatment effects with right-censored data via causal survival forests9
Scalable couplings for the random walk Metropolis algorithm9
Kuldeep Kumar's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng9
Orthogonalized moment aberration for mixed-level multi-stratum factorial designs with partially-relaxed orthogonal block structures9
Bertrand Clarke's contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker9
Anthony C Davison and Igor Rodionov’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas9
Ivor Cribben and Anastasiou Andreas’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’9
Root cause discovery via permutations and Cholesky decomposition8
Tyler J. VanderWeele's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng8
Safaa K. Kadhem's contribution to the Discussion of ‘Augmented balancing weights as linear regression' by Bruns-Smith et al8
Gesine Reinert’s contribution to the Discussion of ‘Statistical exploration of the Manifold Hypothesis’ by Whiteley et al.8
Gradient synchronization for multivariate functional data, with application to brain connectivity8
Identification and estimation of causal peer effects using double negative controls for unmeasured network confounding8
The synthetic instrument: from sparse association to sparse causation8
Penalized empirical likelihood over decentralized networks7
Oliver Hines and Karla Diaz-Ordazʼs Contribution to the Discussion of ‘Assumption-Lean Inference For Generalised Linear Model Parameters’ by Vansteelandt and Dukes7
Ryan Martin’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas7
Simon et al.’s contribution to the Discussion of ‘Statistical exploration of the Manifold Hypothesis’ by Whiteley et al.7
Adaptive functional principal components analysis7
Universal Prediction Band via Semi-Definite Programming7
A general framework for cutting feedback within modularized Bayesian inference7
On the instrumental variable estimation with many weak and invalid instruments7
Martin Larsson and Johannes Ruf’s contribution to the Discussion of ‘Estimating means of bounded random variables by betting’ by Waudby-Smith and Ramdas7
Erratum: Usable and precise asymptotics for generalized linear mixed model analysis and design6
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’6
Sequential model confidence sets6
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 Xu6
Seconder of the vote of thanks to Rohe & Zeng and contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’6
Thorsten Dickhaus’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen6
Least squares for cardinal paired comparisons data6
Kuldeep Kumar’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes6
Autoregressive optimal transport models6
Zihao Wen and David L. Dowe’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen6
Correction to: Consistent and fast inference in compartmental models of epidemics using Poisson Approximate Likelihoods6
Goodness-of-fit tests for high-dimensional Gaussian graphical models via exchangeable sampling6
Yudong Chen and Yining Chen’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’6
Conditional Independence Testing in Hilbert Spaces with Applications to Functional Data Analysis6
Post-detection inference for sequential changepoint localization5
Convexity and measures of statistical association5
α-separability and adjustable combination of amplitude and phase model for functional data5
Inference with Mondrian random forests5
Priyantha Wijayatunga’s contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes, and Walker5
Multi-task learning for sparsity pattern heterogeneity: statistical and computational perspectives5
Model-assisted sensitivity analysis for treatment effects under unmeasured confounding via regularized calibrated estimation5
Ordering factorial experiments5
Correction to: Ordering factorial experiments5
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
Normalised latent measure factor models5
Model privacy: a unified framework for understanding model stealing attacks and defences5
Principal stratification with U-statistics under principal ignorability5
Andrej Srakar’s contribution to the Discussion of ‘Safe testing’ by Grünwald, de Heide, and Koolen5
Semiparametric localized principal stratification analysis with continuous strata5
Interpretable discriminant analysis for functional data supported on random nonlinear domains with an application to Alzheimer’s disease4
Yunxiao Chen and Gongjun Xu's contribution to the Discussion of ‘Vintage Factor Analysis with Varimax Performs Statistical Inference’ by Rohe & Zeng4
CovNet: Covariance Networks for Functional Data on Multidimensional Domains4
Semi-parametric tensor factor analysis by iteratively projected singular value decomposition4
Estimating means of bounded random variables by betting4
Stratification pattern enumerator and its applications4
Scalable Bayesian inference for heat kernel Gaussian processes on manifolds4
Trace-class Gaussian priors for Bayesian learning of neural networks with MCMC4
Jiaqi Gu and Guosheng Yin’s contribution to the Discussion of ‘Martingale Posterior Distributions’ by Fong, Holmes and Walker4
Combining evidence across filtrations4
Sparse Kronecker product decomposition: a general framework of signal region detection in image regression4
Autoregressive networks with dependent edges4
Peng Ding’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes4
Multi-resolution subsampling for linear classification with massive data4
Debiased inference for a covariate-adjusted regression function4
Contents of Volume 84, 20224
Shakeel Gavioli-Akilagun’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’4
Ensemble methods for testing a global null4
Analytic natural gradient updates for Cholesky factor in Gaussian variational approximation4
Correction to: Holdout predictive checks for Bayesian model criticism4
Derandomised knockoffs: leveraging e-values for false discovery rate control4
Graphical methods for Order-of-Addition experiments4
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