Annual Review of Statistics and Its Application

238 papers and 8.4k indexed citations i.

About

The 238 papers published in Annual Review of Statistics and Its Application in the last decades have received a total of 8.4k indexed citations. Papers published in Annual Review of Statistics and Its Application usually cover Statistics and Probability (108 papers), Artificial Intelligence (76 papers) and Management Science and Operations Research (27 papers) specifically the topics of Statistical Methods and Inference (55 papers), Statistical Methods and Bayesian Inference (49 papers) and Advanced Causal Inference Techniques (30 papers). The most active scholars publishing in Annual Review of Statistics and Its Application are Tilmann Gneiting, Matthias Katzfuß, Larry Wasserman, Jeffrey S. Morris, Ruslan Salakhutdinov, Hongzhe Li, Eric B. Laber, Jane-Ling Wang, Jeng‐Min Chiou and Hans‐Georg Müller.

In The Last Decade

Fields of papers published in Annual Review of Statistics and Its Application

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Annual Review of Statistics and Its Application. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Annual Review of Statistics and Its Application.

Countries where authors publish in Annual Review of Statistics and Its Application

Since Specialization
Citations

This map shows the geographic impact of research published in Annual Review of Statistics and Its Application. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Annual Review of Statistics and Its Application with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Annual Review of Statistics and Its Application more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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