Annual Review of Statistics and Its Application

Annual Review of Statistics and Its Application

ISSN: 2326-8298
eISSN: 2326-831X

AIMS AND SCOPE OF JOURNAL: The Annual Review of Statistics and Its Application informs statisticians, and users of statistics about major methodological advances and the computational tools that allow for their implementation.

Published Since

2014

Journal Status

Active

Impact Factor	7.4

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- Tensors in High-Dimensional Data Analysis: Methodological Opportunities and Theoretical Challenges
  
  Arnab Auddy, Dong Xia and Ming Yuan
  
  Vol. 12 (2025), pp. 527–551
- Generalized Additive Models
  
  Simon N. Wood
  
  Vol. 12 (2025), pp. 497–526
- A Theoretical Review of Modern Robust Statistics
  
  Po-Ling Loh
  
  Vol. 12 (2025), pp. 477–496
- Joint Modeling of Longitudinal and Survival Data
  
  Jane-Ling Wang and Qixian Zhong
  
  Vol. 12 (2025), pp. 449–476
- Empirical Likelihood in Functional Data Analysis
  
  Hsin-wen Chang and Ian W. McKeague
  
  Vol. 12 (2025), pp. 425–448
- Demystifying Inference After Adaptive Experiments
  
  Aurélien Bibaut and Nathan Kallus
  
  Vol. 12 (2025), pp. 407–423
- Identification and Inference with Invalid Instruments
  
  Hyunseung Kang, Zijian Guo, Zhonghua Liu and Dylan Small
  
  Vol. 12 (2025), pp. 385–405
- High-Dimensional Gene–Environment Interaction Analysis
  
  Mengyun Wu, Yingmeng Li and Shuangge Ma
  
  Vol. 12 (2025), pp. 361–383
- Causal Mediation Analysis for Integrating Exposure, Genomic, and Phenotype Data
  
  Haoyu Yang, Zhonghua Liu, Ruoyu Wang, En-Yu Lai, Joel Schwartz, Andrea A. Baccarelli, Yen-Tsung Huang and Xihong Lin
  
  Vol. 12 (2025), pp. 337–360
- Neural Methods for Amortized Inference
  
  Andrew Zammit-Mangion, Matthew Sainsbury-Dale and Raphaël Huser
  
  Vol. 12 (2025), pp. 311–335
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- Functional Data Analysis
  
  Jane-Ling Wang, Jeng-Min Chiou and Hans-Georg Müller
  
  Vol. 3 (2016), pp. 257–295
- Probabilistic Forecasting
  
  Tilmann Gneiting and Matthias Katzfuss
  
  Vol. 1 (2014), pp. 125–151
- Bayesian Computing with INLA: A Review
  
  Håvard Rue, Andrea Riebler, Sigrunn H. Sørbye, Janine B. Illian, Daniel P. Simpson and Finn K. Lindgren
  
  Vol. 4 (2017), pp. 395–421
- Algorithmic Fairness: Choices, Assumptions, and Definitions
  
  Shira Mitchell, Eric Potash, Solon Barocas, Alexander D'Amour and Kristian Lum
  
  Vol. 8 (2021), pp. 141–163
- Finite Mixture Models
  
  Geoffrey J. McLachlan, Sharon X. Lee and Suren I. Rathnayake
  
  Vol. 6 (2019), pp. 355–378
- Functional Regression
  
  Jeffrey S. Morris
  
  Vol. 2 (2015), pp. 321–359
- Topological Data Analysis
  
  Larry Wasserman
  
  Vol. 5 (2018), pp. 501–532
- Q-Learning: Theory and Applications
  
  Jesse Clifton and Eric Laber
  
  Vol. 7 (2020), pp. 279–301
- Statistical Aspects of Wasserstein Distances
  
  Victor M. Panaretos and Yoav Zemel
  
  Vol. 6 (2019), pp. 405–431
- Granger Causality: A Review and Recent Advances
  
  Ali Shojaie and Emily B. Fox
  
  Vol. 9 (2022), pp. 289–319
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Annual Review of Statistics and Its Application

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