Journal Statistics

180
Journal of the Royal Statistical Society Series B
papers tracked
409
Journal of the American Statistical Association
papers tracked
162
Annals of Statistics
papers tracked
115
Biometrika
papers tracked
320
Journal of Machine Learning Research
papers tracked

Recent Papers

JASA Jun 23, 2026
Interpretable Scalar-on-Image Linear Regression Models via the Generalized Dantzig Selector

Sijia Liao, Xiaoxiao Sun, Ning Hao et al.

Machine Learning
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JASA Jun 23, 2026
Anytime-Valid Inference in Linear Models with Applications to Regression-Adjusted Causal Inference

Michael Lindon, Dae Woong Ham, Martin Tingley et al.

Causal Inference Machine Learning
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JASA Jun 23, 2026
Optimally adaptive test for high dimensional hypotheses via minimax deficiency

Yumou Qiu, Jingkun Qiu, Song Xi Chen

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JRSSB Jun 23, 2026
Structural classification of locally stationary time series based on second-order characteristics

Xiucai Ding, Lexin Li, Chen Qian

Machine Learning Time Series
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JASA Jun 23, 2026
Causal Inference with Generative Artificial Intelligence: Application to Texts as Treatments*

Kosuke Imai, Kentaro Nakamura

Causal Inference Machine Learning
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JRSSB Jun 23, 2026
On the statistical analysis of grouped data: when Pearson χ2 and other divisible statistics are not goodness-of-fit

Sara Algeri, Estate V Khmaladze

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JRSSB Jun 22, 2026
I-Chen Lee and Weng-Kee Wong’s contribution to the Discussion of ‘Regression by composition’ by Farewell et al

Lee I-Chen, Weng-Kee Wong

Machine Learning
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AOS Jun 20, 2026
Spectral Asymptotics of Neural Network Jacobians: Convergency, Universality, and Phase Transition

Guangming Pan, Huiqin Li, Yanqing Yin

Machine Learning
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JRSSB Jun 20, 2026
Fukang Zhu’s contribution to the Discussion of ‘Regression by composition’ by Farewell et al

Fukang Zhu

Machine Learning
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JRSSB Jun 20, 2026
Davison’s contribution to the discussion of ‘Regression by composition’ by Farewell et al

Anthony C Davison

Machine Learning
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JRSSB Jun 20, 2026
Vern T Farewell’s contribution to the Discussion of ‘Regression by composition’ by Farewell et al

Vernon T Farewell

Machine Learning
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JRSSB Jun 20, 2026
Heather Battey’s invited contribution to the discussion of ‘Regression by composition’ by Farewell et al

Heather Battey

Machine Learning
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Biometrika Jun 18, 2026
Quasi-Bayes empirical Bayes: a sequential approach to the Poisson compound decision problem

S Favaro, S Fortini

Bayesian Statistics
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Biometrika Jun 18, 2026
Inference on covariance structure in high-dimensional multi-view data

D B Dunson, L Mauri

High-Dimensional Statistics
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JASA Jun 17, 2026
Structured Mixture of Continuation-ratio Logits Models for Ordinal Regression

Athanasios Kottas, Jizhou Kang

Machine Learning
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JRSSB Jun 17, 2026
López de Prado and Porcu’s contribution to the Discussion of ‘Regression by compositio’ by Farewell et al

Emilio Porcu, Marcos López de Prado

Machine Learning
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JASA Jun 17, 2026
Scalable calibration of individual-based epidemic models through categorical approximations

Nick Whiteley, Lorenzo Rimella, Michael Whitehouse et al.

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JASA Jun 17, 2026
Channeling Multimodality Through a Unimodalizing Transport: Warp-U Sampler and Stochastic Bridge Sampling Estimator

Shiyuan He, Fei Ding, David E. Jones et al.

High-Dimensional Statistics
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AOS Jun 16, 2026
Nuisance Function Tuning and Sample Splitting for Optimally Estimating a Doubly Robust Functional

Rajarshi Mukherjee, Sean McGrath

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JRSSB Jun 16, 2026
Safaa K Kadhem's contribution to the Discussion of ‘Regression by composition’ by Farewell et al

Safaa K Kadhem

Machine Learning
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