Adrian E. Raftery

Adrian is the Boeing International Professor of Statistics and Sociology, and Adjunct Professor of Atmospheric Sciences at the University of Washington. He is also a faculty affiliate of the Center for Statistics and the Social Sciences and the Center for Studies in Demography and Ecology. He works on the development of new statistical methods for the social and environmental sciences. An elected member of the U.S. National Academy of Sciences, he was identified as the world's most cited researcher in mathematics for the decade 1995-2005 by Thomson-ISI. He has supervised 32 Ph.D. graduates, of whom 21 hold or have held tenure-track university faculty positions.

• Working Group on Model-Based Clustering, Pittsburgh, July 17-21, 2023
• Twitter feed

New book on mclust and model-based clustering:

News

• Website update: This website got its annual major update on May 10, 2023. New publications were added.
• New York Times interactive feature: The NYT published the interactive feature Extreme Heat Will Change Us, based on our research in Zeppetello, Raftery and Battisti (2022).
• Adrian gave the Jacques Morgenstern Colloquium at INRIA, Sophia-Antipolis, France, in April 2023.
• Adrian gave the first HITS-IMK Joint Colloquium at the Heidelberg Institute for Theoretical Study, Heidelberg, Germany, in April 2023.
• Adrian gave the Economics, Mathematics and Statistics Distinguished Lecture at University College Dublin in April 2023.

Recent Journal Articles and Preprints (since 2022)

Statistical climate science

• Comprehensive New Evidence Implies a Higher Social Cost of CO₂.
• The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates.
• A Dangerous Future: Probabilistic Projections of Increased Heat Stress Driven By Global Climate Change.
• Long-Term Probabilistic Temperature Projections for All Locations.

Statistical demography

• Probabilistic Estimation and Projection of the Annual Total Fertility Rate Accounting for Past Uncertainty.
• Probabilistic Population Forecasting: Short to Very Long Term.
• Probabilistic Forecasts of International Bilateral Migration Flows.

Statistical methodology

• Effect of model space priors on statistical inference with model uncertainty.
• Comparing methods for statistical inference with model uncertainty.
• Model-Based Clustering.
• Contour Models for Physical Boundaries Enclosing Star-Shaped and Approximately Star-Shaped Polygons. Preprint.
• Balancing Inferential Integrity and Disclosure Risk via Model Targeted Masking and Multiple Imputation.

These papers are being made available here to facilitate the timely dissemination of scholarly work; copyright and all related rights are retained by the copyright holders.

Last major update, May 11, 2023.

Copyright 2005-2023 by Adrian E. Raftery and University of Washington; all rights reserved.