Daniel Barry

1.6k citations
28 papers · 1.0k indexed · h-index 10

Impact in

    • Statistical Methods and Inference
    • Statistical Methods and Bayesian Inference
    • Advanced Statistical Methods and Models
  • Paleontology top 10%
    • Evolution and Paleontology Studies

Papers in

Daniel Barry

26 papers receiving 945 citations

Peers

Daniel Barry
Comparison fields: 5 of 140
  • Statistics and Probability 301
  • Paleontology 71
  • Artificial Intelligence 271
  • Statistics, Probability and Uncertainty 54
  • Finance 72
Replace Ana Justel with:
Ana Justel Spain
Richard Lockhart Canada
Chunsheng Ma United States
Friedrich Schmid Germany
Jeffrey D. Banfield United States
Sadanori Konishi Japan
A. F. M. Smith United Kingdom
Allan McQuarrie United States
Murray Jorgensen New Zealand
Hilary L. Seal Switzerland
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Barry

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Barry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Daniel Barry, 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 Daniel Barry Line = papers co-authored together Daniel Barry links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993455
2 1992191
3 1987125
4 198770
5 198645
6 199323
7 199319
8 199018
9 199715
10 20089
11 19968
12 19938
13 20076
14 20056
15 19875
16 20215
17 20023
18 20242
19 19922
20 20021

About Daniel Barry

Daniel Barry is a scholar working on Statistics and Probability, Economics and Econometrics, Artificial Intelligence, Computer Networks and Communications and Hardware and Architecture, having authored 28 papers that have together received 1.0k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (9 papers), Advanced Statistical Methods and Models (6 papers), Statistical Methods and Inference (5 papers), Sports Analytics and Performance (5 papers), Consumer Market Behavior and Pricing (3 papers), Parallel Computing and Optimization Techniques (3 papers), Nutritional Studies and Diet (2 papers) and Advanced Data Storage Technologies (2 papers). The work is most often cited by research in Statistics and Probability (301 citations), Paleontology (71 citations), Artificial Intelligence (271 citations), Statistics, Probability and Uncertainty (54 citations) and Finance (72 citations). Daniel Barry has collaborated with scholars based in Ireland, United States and New Zealand. Frequent co-authors include J. A. Hartigan, Avril Hegarty, Michael Hogan, Graeme Woodward, Andreas Willig, Vicki Livingstone, Anthony Danalis, Wolfgang Karl Härdle, Jack Dongarra and W.A. Lane. Their work appears in journals such as The Annals of Statistics, Journal of the American Statistical Association, Journal of Applied Probability, Statistics in Medicine and Statistical Science.

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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