Diego Kuonen

560 citations
18 papers · 403 · h-index 8

Impact in

Papers in

Diego Kuonen

17 papers receiving 375 citations

Peers

Diego Kuonen
Comparison fields: 5 of 103
  • Ecological Modeling 36
  • Statistics and Probability 49
  • Virology 22
  • Cellular and Molecular Neuroscience 53
  • Ecology, Evolution, Behavior and Systematics 54
Replace Christian Mazza with:
Christian Mazza Switzerland
Jane‐Ling Wang United States
Colin Rundel United States
Chong He United States
Aluísio Pinheiro Brazil
Ted H. Emigh United States
Kamil Erguler Cyprus
Frank Dondelinger United Kingdom
Gilles Didier France
Karen Cranston United States
Diego Kuonen relative to Christian Mazza Switzerland Christian Mazza's profile →
Citations per field
00.5×10×15×22×
Christian Mazza · 1×
Citations per year

Countries citing papers authored by Diego Kuonen

Since Specialization
Citations

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

Fields of papers citing papers by Diego Kuonen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Diego Kuonen, 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 Diego Kuonen Line = papers co-authored together Diego Kuonen links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 1999108
2 198170
3 200167
4 200447
5 200129
6
An introduction to the bootstrap with applications in R
200223
7
Challenges in Bioinformatics for Statistical Data Miners
200316
8 200315
9 20047
10 20016
11 20053
12 20003
13 20193
14 20222
15 20012
16
Numerical Integration in S-PLUS or R: A Survey
20031
17 20051
18
Is Data Mining for Gold "Statistical déjà vu"?
20050

About Diego Kuonen

Diego Kuonen is a scholar working on Statistics and Probability, Artificial Intelligence, Management Information Systems, Information Systems and Ecology, Evolution, Behavior and Systematics, having authored 18 papers that have together received 403 indexed citations. Recurring topics across this work include Statistical Methods and Inference (4 papers), Advanced Statistical Methods and Models (3 papers), Data Mining Algorithms and Applications (2 papers), Statistical Methods and Bayesian Inference (2 papers), Immune Cell Function and Interaction (2 papers), Big Data and Business Intelligence (2 papers), Scientific Research and Discoveries (2 papers) and Botany and Plant Ecology Studies (1 paper). The work is most often cited by research in Ecological Modeling (36 citations), Statistics and Probability (49 citations), Virology (22 citations), Cellular and Molecular Neuroscience (53 citations) and Ecology, Evolution, Behavior and Systematics (54 citations). Diego Kuonen has collaborated with scholars based in Switzerland, Italy and Finland. Frequent co-authors include Alessandro Massolo, Rodolphe Schlaepfer, Christian Glenz, A. C. Davison, L.F. Agnati, Sven Ove Ögren, K. Andersson, Tomas Hökfelt, C. Köhler and Kjell Fuxé. Their work appears in journals such as Clinical & Experimental Immunology, Heredity, Quality Engineering, The American Statistician and Journal of Neural Transmission.

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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