Malcolm Farrow

42 papers receiving 495 citations

Peers

Malcolm Farrow
Comparison fields: 5 of 144
  • Software 34
  • Statistics and Probability 43
  • Dermatology 40
  • Statistics, Probability and Uncertainty 26
  • Paleontology 24
Replace Laurence L. George with:
Laurence L. George United States
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Daniel Lee United States
Giuseppe Casalicchio Germany
K. D. S. Young United Kingdom
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Elizabeth González‐Estrada Mexico
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Malcolm Farrow relative to Laurence L. George United States Laurence L. George's profile →
Citations per field
00.5×10×
Laurence L. George · 1×
Citations per year

Countries citing papers authored by Malcolm Farrow

Since Specialization
Citations

This map shows the geographic impact of Malcolm Farrow'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 Malcolm Farrow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Malcolm Farrow more than expected).

Fields of papers citing papers by Malcolm Farrow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Malcolm Farrow. 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 Malcolm Farrow. The network helps show where Malcolm Farrow may publish in the future.

Co-authors

The 25 scholars most cited alongside Malcolm Farrow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Malcolm Farrow Line = papers co-authored together Malcolm Farrow links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199948
2 200147
3 200643
4 201835
5 198834
6 198532
7 200927
8 200625
9 201223
10 200622
11 198818
12 202015
13 200313
14 200212
15 199312
16 200611
17 199310
18 20059
19 20159
20 20049

About Malcolm Farrow

Malcolm Farrow is a scholar working on Statistics and Probability, Artificial Intelligence, Information Systems, Software and Management Science and Operations Research, having authored 43 papers that have together received 529 indexed citations. Recurring topics across this work include Software Engineering Research (6 papers), Software Reliability and Analysis Research (6 papers), Statistical Methods and Bayesian Inference (4 papers), Bayesian Modeling and Causal Inference (4 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (4 papers), Plant and animal studies (3 papers), Bayesian Methods and Mixture Models (3 papers) and Risk and Safety Analysis (2 papers). The work is most often cited by research in Software (34 citations), Statistics and Probability (43 citations), Dermatology (40 citations), Statistics, Probability and Uncertainty (26 citations) and Paleontology (24 citations). Malcolm Farrow has collaborated with scholars based in United Kingdom, Germany and Iraq. Frequent co-authors include Wallace Arthur, Michael Oakes, Warren Gilchrist, Michael Goldstein, Brian K. Saxby, Kevin J. Wilson, Margaret Bell, Allan Carmichael, Dilum Dissanayake and Graham Burns. Their work appears in journals such as Software Quality Journal, Journal of the Royal Statistical Society Series C (Applied Statistics), International Journal of Approximate Reasoning, Information and Software Technology and The Medical Journal of Australia.

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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