Handbook of Markov Chain Monte Carlo
- Journal
- arXiv (Cornell University)
In The Last Decade
doi.org/10.1201/b10905 →Countries where authors are citing Handbook of Markov Chain Monte Carlo
This map shows the geographic impact of Handbook of Markov Chain Monte Carlo. 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 Handbook of Markov Chain Monte Carlo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Handbook of Markov Chain Monte Carlo more than expected).
Fields of papers citing Handbook of Markov Chain Monte Carlo
This network shows the impact of Handbook of Markov Chain Monte Carlo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Handbook of Markov Chain Monte Carlo.
About Handbook of Markov Chain Monte Carlo
This paper, published in 2011, received 1.9k indexed citations . Written by Steve Brooks, Andrew Gelman, Galin L. Jones and Xiao‐Li Meng covering the research area of Statistics and Probability. It is primarily cited by scholars working on Artificial Intelligence (503 citations), Statistics and Probability (490 citations) and Statistics, Probability and Uncertainty (192 citations). Published in arXiv (Cornell University).
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.
This paper is also available at doi.org/10.1201/b10905.