Robert J. B. Goudie
- Artificial Intelligence
- Statistics and Probability top 5%
- Economics and Econometrics
- Social Psychology
- Infectious Diseases
- Co-authors
- Sach MukherjeeDaniela De AngelisRebecca TurnerAndrew C. ThomasStephen WuJan‐Emmanuel De NeveAndrew J. OswaldDavid J. Lunn
- Topics
- Statistical Methods and Bayesian Inference (8 papers)Bayesian Methods and Mixture Models (7 papers)COVID-19 and healthcare impacts (5 papers)
- Journals
- PLoS ONEBiometricsBiometrika
- Partner nations
- United KingdomUnited StatesSouth Sudan
In The Last Decade
Robert J. B. Goudie
25 papers receiving 215 citations
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 65
- Statistics and Probability 59
- Economics and Econometrics 30
- Social Psychology 27
- Infectious Diseases 17
Countries citing papers authored by Robert J. B. Goudie
This map shows the geographic impact of Robert J. B. Goudie's research. 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 Robert J. B. Goudie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert J. B. Goudie more than expected).
Fields of papers citing papers by Robert J. B. Goudie
This network shows the impact of papers produced by Robert J. B. Goudie. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Robert J. B. Goudie. The network helps show where Robert J. B. Goudie may publish in the future.
Co-authorship network of co-authors of Robert J. B. Goudie
This figure shows the co-authorship network connecting the top 25 collaborators of Robert J. B. Goudie. A scholar is included among the top collaborators of Robert J. B. Goudie based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Robert J. B. Goudie. Robert J. B. Goudie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 6 | |
| 9 | 6 | |
| 10 | 4 | |
| 11 | 2 | |
| 12 | 18 | |
| 13 | 10 | |
| 14 | 37 | |
| 15 | MultiBUGS: Massively parallel MCMC for Bayesian hierarchical models | 4 |
| 16 | 32 | |
| 17 | 4 | |
| 18 | Exploratory network analysis of large social science questionnaires | 1 |
| 19 | 2 | |
| 20 | 2 |
About Robert J. B. Goudie
Robert J. B. Goudie is a scholar working on Statistics and Probability, General Decision Sciences and Geriatrics and Gerontology, having authored 28 papers that have together received 221 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (8 papers), Bayesian Methods and Mixture Models (7 papers) and COVID-19 and healthcare impacts (5 papers). The work is most often cited by research in Statistics and Probability (59 citations), General Decision Sciences (6 citations) and Modeling and Simulation (14 citations). Robert J. B. Goudie has collaborated with scholars based in United Kingdom, United States and South Sudan. Frequent co-authors include Sach Mukherjee, Daniela De Angelis, Rebecca Turner, Andrew C. Thomas, Stephen Wu, Jan‐Emmanuel De Neve, Andrew J. Oswald, David J. Lunn, Jacobus Preller and Brian D. M. Tom. Their work appears in journals such as PLoS ONE, Biometrics and Biometrika.
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.