David Smith
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Bayesian Inference
- Statistical Methods in Clinical Trials
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- Insect and Pesticide Research
- Entomopathogenic Microorganisms in Pest Control
Papers in
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- Statistical Methods and Bayesian Inference 4
- Statistical Methods and Inference 2
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- Plant and animal studies 2
- Fossil Insects in Amber 2
- Co-authors
- W. N. Venables (1 shared paper)M. J. Faddy (2 shared papers)Peter J. Diggle (1 shared paper)Byron J. T. Morgan (1 shared paper)Tikahiko Naito (1 shared paper)Simon Pack (1 shared paper)
- Journals
- Journal of Statistical Software (2 papers)Statistics in Medicine (1 paper)Computer Methods and Programs in Biomedicine (1 paper)Journal of Hymenoptera Research (1 paper)Repository of the University of Ljubljana (University of Ljubljana) (1 paper)
- Partner nations
- AustraliaUnited KingdomRussia
In The Last Decade
David Smith
7 papers receiving 278 citations
Peers
Comparison fields: 5 of 127
- Statistics and Probability 49
- Insect Science 39
- Family Practice 4
- Management Science and Operations Research 21
- Ecology, Evolution, Behavior and Systematics 28
Countries citing papers authored by David Smith
This map shows the geographic impact of David Smith'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 David Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Smith more than expected).
Fields of papers citing papers by David Smith
This network shows the impact of papers produced by David Smith. 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 David Smith. The network helps show where David Smith may publish in the future.
Co-authors
The 6 scholars most cited alongside David Smith, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | An introduction to R | 2004 | 290 |
| 2 | 2016 | 10 | |
| 3 | 1998 | 9 | |
| 4 | 1975 | 4 | |
| 5 | 1989 | 4 | |
| 6 | The insect remains | 2015 | 4 |
| 7 | 2015 | 2 | |
| 8 | 2019 | 0 |
About David Smith
David Smith is a scholar working on Statistics and Probability, Ecology, Evolution, Behavior and Systematics, Artificial Intelligence, Management Science and Operations Research and Genetics, having authored 8 papers that have together received 323 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (4 papers), Plant and animal studies (2 papers), Statistical Methods and Inference (2 papers), Fossil Insects in Amber (2 papers), Genetic and phenotypic traits in livestock (1 paper), Insect Utilization and Effects (1 paper), Advanced Statistical Process Monitoring (1 paper) and demographic modeling and climate adaptation (1 paper). The work is most often cited by research in Statistics and Probability (49 citations), Insect Science (39 citations), Family Practice (4 citations), Management Science and Operations Research (21 citations) and Ecology, Evolution, Behavior and Systematics (28 citations). David Smith has collaborated with scholars based in Australia, United Kingdom and Russia. Frequent co-authors include W. N. Venables, M. J. Faddy, Peter J. Diggle, Byron J. T. Morgan, Tikahiko Naito and Simon Pack. Their work appears in journals such as Journal of Statistical Software, Statistics in Medicine, Computer Methods and Programs in Biomedicine, Journal of Hymenoptera Research and Repository of the University of Ljubljana (University of Ljubljana).
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.