International Statistical Review

1997 - 2026

Current editor(s): Eugene Seneta and Kees Zeelenberg

From International Statistical Institute
Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

Access Statistics for this journal.
Is something missing from the series or not right? See the RePEc data check for the archive and series.

Volume 94, issue 2, 2026

A Conversation With David Bellhouse pp. 221-241

Christian Genest

A New Evaluation Strategy for Diagnostic Tests Under Umbrella or Tree Ordering pp. 242-263

Duc‐Khanh To, Gianfranco Adimari and Monica Chiogna

An Uncertainty Based Approach for Dealing With Selection Bias in Non‐Probability Samples pp. 264-290

Pier Luigi Conti and Daniela Marella

Recent Developments on Statistical Transfer Learning pp. 291-324

Zhengyu Zhu, Yibo Yan, Gefei Li and Riquan Zhang

On Metric Choice in Dimension Reduction for Fréchet Regression pp. 325-346

Abdul‐Nasah Soale, Congli Ma, Siyu Chen and Obed Koomson

A Comparative Review of Specification Tests for Diffusion Models pp. 347-381

A. López‐Pérez, D. Diz‐Castro, M. Febrero‐Bande and W. González‐Manteiga

Medical Knowledge Integration Into Reinforcement Learning Algorithms for Dynamic Treatment Regimes pp. 382-411

Sophia Yazzourh, Nicolas Savy, Philippe Saint‐Pierre and Michael R. Kosorok

Inference via Robust Optimal Transportation: Theory and Methods pp. 412-444

Yiming Ma, Hang Liu, Davide La Vecchia and Matthieu Lerasle

Pre‐Smoothing Methods for Transition Probabilities in Complex Non‐Markovian Multistate Models pp. 445-463

Gustavo Soutinho and Luís Meira‐Machado

The Role of Dice in the Emergence of the Probability Calculus pp. 464-483

David R. Bellhouse and Christian Genest

New Perspectives in Mathematical and Statistical Methods for Actuarial Sciences and Finance, Michele La Rocca, Massimiliano Menzietti, Cira Perna, and Marilena Sibillo, Springer Nature Switzerland AG, 2025, viii + 261 pages, £119.99, hardcover. ISBN: 978‐3‐032‐05550‐7 (print); 978‐3‐032‐05551‐4 (eBook) pp. 484-485

Svetlozar Rachev

Data Science and Risk Analytics in Finance and Insurance, Tze Leung Lai and Haipeng Xing, Chapman & Hall/CRC Financial Mathematics Series, 2024, 366 pages, $99.99, hardcover; $94.99, Kindle. ISBN: 978‐1‐4398‐3948‐5 pp. 486-487

Svetlozar Rachev

Machine Learning in Finance: Trends, Developments and Business Practices in the Financial Sector Musa Gun and Burcu Kartal Springer Nature Switzerland AG, 2025, xi + 204 pages, £149.99, hardcover ISBN: 978‐3‐031‐83265‐9 (print); 978‐3‐031‐83266‐6 (eBook) pp. 487-489

Svetlozar Rachev

Fundamentals of Robust Machine Learning: Handling Outliers and Anomalies in Data Science Resve Saleh, Sohaib Majzoub, A.K. Md. Ehsanes Saleh John Wiley & Sons, 2025, xiv + 416 pages, £103.95, hardcover ISBN: 978‐1‐394‐29437‐4 pp. 489-491

Zhilin Xiong and Tiefeng Ma

Master Protocol Clinical Trials for Evidence Generation: Strategies, Designs, Operations and Case Studies. Ruixiao Lu, Jingjing Ye, Chengxing (Cindy) Lu, William Wang, Chapman & Hall. CRC Biostatistics Series, 2026, 436 pages, £140.00, hardcover ISBN: 978‐1‐032‐54452‐6 pp. 491-492

Debashis Ghosh

A First Course in Statistical Learning, With Data Examples and Python Code Johannes Lederer Springer, 2025, xiv + 282 pages, £79.99, hardcover ISBN: 978‐3‐031‐30276‐3 pp. 492-493

Rauf Ahmad

Machine Learning: A Concise Introduction, 2nd Edition, Steven W. Knox. Wiley, 2026, xiv + 419 pages, $109.95, hardcover. ISBN: 978‐1‐394‐32525‐2 pp. 494-495

Alastair Young

High‐dimensional Probability: An Introduction with applications in data science, 2nd Edition Roman Vershynin Cambridge University Press, 2026, viii + 333 pages, £65, hardcover ISBN: 9781009490672 pp. 495-496

Rauf Ahmad

Applied Time Series Analysis for the Social Sciences: Specification, Estimation and Inference. Regina M. Baker. John Wiley & Sons, 2026, xiii + 226 pages, $76.95, hardcover. ISBN: 9780470749937 pp. 497-497

Johan Lyhagen

Bayesian Workflow Andrew Gelman, Aki Vehtari, and Richard McElreath, with Daniel Simpson, Charles C. Margossian, Yuling Yao, Lauren Kennedy, Jonah Gabry, Paul‐Christian Bürkner, Martin Modrák, and Vianey Leos Barajas CRC Press, 2026, xiii + 538 pages, $59.99/£35.99, paperback ISBN: 978‐0‐367‐49014‐0 pp. 498-499

Alastair Young

Volume 94, issue 1, 2026

Robust Distance Covariance pp. 1-25

Sarah Leyder, Jakob Raymaekers and Peter J. Rousseeuw

Comparing Robust Versions of Distance Covariance: A Comment on the Biloop Approach pp. 26-34

Dominic Edelmann

Discussion to the paper ‘Robust Distance Covariance’ pp. 34-40

Klaus Nordhausen and Una Radojičić

Discussion of ‘Robust distance covariance’ by S. Leyder, J. Raymaekers and P. J. Rousseeuw pp. 40-53

Hallin Marc, Davide La Vecchia, Hang Liu and Xinyi Xu

Rejoinder pp. 53-60

Sarah Leyder, Jakob Raymaekers and Peter J. Rousseeuw

Flexible Multivariate Mixture Models: A Comprehensive Approach for Modeling Mixtures of Non‐Identical Distributions pp. 61-96

Samyajoy Pal and Christian Heumann

Alternative Approaches for Estimating Highest‐Density Regions pp. 97-120

Nina Deliu and Brunero Liseo

On Frequency and Probability Weights: An In‐Depth Look at Duelling Weights pp. 121-139

Tuo Lin, Ruohui Chen, Jinyuan Liu, Tsungchin Wu, Toni T. Gui, Yangyi Li, Xinyi Huang, Kun Yang, Guanqing Chen, Tian Chen, David R. Strong, Karen Messer and Xin M. Tu

Handling Out‐of‐Sample Areas to Estimate the Unemployment Rate at Local Labour Market Areas in Italy pp. 140-162

Roberto Benedetti, Federica Piersimoni, Monica Pratesi, Nicola Salvati and Thomas Suesse

Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels pp. 163-187

Wei Jing, Michail Papathomas and Silvia Liverani

Fisher Meets Bayes: The Value of Randomisation for Bayesian Inference of Causal Effects pp. 188-201

Thomas Leavitt

Adjusting Self‐Protective and Non‐Response Behaviours in Sensitive Prevalence Estimation by a Two‐Stage Multilevel Randomised Response Technique pp. 202-220

Martin T. Lukusa, Pier Francesco Perri and Shu‐Hui Hsieh

Volume 93, issue 3, 2025

A Socio‐demographic Latent Space Approach to Spatial Data When Geography Is Important But not All‐Important pp. 351-373

Saikat Nandy, Scott H. Holan and Michael Schweinberger

Invited Discussion on Article by Nandy, Holan and Schweinberger pp. 374-376

Jonathan Bradley

Who Is My Neighbour? A Discussion of ‘A Socio‐Demographic Latent Space Approach to Spatial Data When Geography Is Important but Not All‐Important’ pp. 377-380

Lance A. Waller

Rejoinder: A Socio‐Demographic Latent Space Approach to Spatial Data When Geography is Important but Not All‐Important pp. 380-384

Saikat Nandy, Scott H. Holan and Michael Schweinberger

Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions pp. 385-424

Nina Deliu, Joseph Jay Williams and Bibhas Chakraborty

Clustering Longitudinal Data: A Review of Methods and Software Packages pp. 425-458

Zihang Lu

New Scheme of Empirical Likelihood Method for Ranked Set Sampling: Applications to Two One‐Sample Problems pp. 459-498

Soohyun Ahn, Xinlei Wang, Chul Moon and Johan Lim

Validating an Index of Selection Bias for Proportions in Non‐Probability Samples pp. 499-516

Angelina Hammon and Sabine Zinn

Statistical Analysis of Data Repeatability Measures pp. 517-543

Zeyi Wang, Eric Bridgeford, Shangsi Wang, Joshua T. Vogelstein and Brian Caffo

Volume 93, issue 2, 2025

A Conversation With Amy Racine‐Poon pp. 183-198

Oleksandr Sverdlov

Chance‐Corrected Interrater Agreement Statistics for Two‐Rater Dichotomous Responses: A Method Review With Comparative Assessment Under Possibly Correlated Decisions pp. 199-221

Zizhong Tian, Vernon M. Chinchilli, Chan Shen and Shouhao Zhou

On the Number of Components for Matrix‐Variate Mixtures: A Comparison Among Information Criteria pp. 222-245

Salvatore D. Tomarchio and Antonio Punzo

Revisiting Estimation of Number of Trials in Binomial Distribution pp. 246-266

Mina Georgieva and Brani Vidakovic

Feature Screening for Ultrahigh Dimensional Mixed Data via Wasserstein Distance pp. 267-287

Bing Tian and Hong Wang

How Do Applied Researchers Use the Causal Forest? A Methodological Review pp. 288-316

Patrick Rehill

Statistical Depth Meets Machine Learning: Kernel Mean Embeddings and Depth in Functional Data Analysis pp. 317-348

George Wynne and Stanislav Nagy

Volume 93, issue 1, 2025

An Interview With Peter Rousseeuw pp. 1-17

Mia Hubert

A Survey of Monte Carlo Methods for Noisy and Costly Densities With Application to Reinforcement Learning and ABC pp. 18-61

Fernando Llorente, Luca Martino, Jesse Read and David Delgado‐Gómez

Small Sample Inference for Two‐Way Capture‐Recapture Experiments pp. 62-72

Louis‐Paul Rivest and Mamadou Yauck

The Raise Regression: Justification, Properties and Application pp. 73-101

Román Salmerón‐Gómez, Catalina B. García‐García and José García‐Pérez

Joint Robust Variable Selection of Mean and Covariance Model via Shrinkage Methods pp. 102-129

Yeşim Güney, Fulya Gokalp Yavuz and Olcay Arslan

An Optimised Optional Randomised Response Technique pp. 130-149

Kavya Pushadapu, Sarjinder Singh and Stephen A. Sedory

Summary characteristics for multivariate function‐valued spatial point process attributes pp. 150-178

Matthias Eckardt, Carles Comas and Jorge Mateu

Data Analytics and Machine Learning: Navigating the Big Data Landscape Edited by Pushpa Singh, Asha Rani Mishra, and Payal Garg Springer, 2024, 366 pages, $169.99, hardcover ISBN: 978‐9819704477 pp. 179-182

Brian W. Sloboda