Eva Cantoni

2.0k citations
46 papers · 1.5k · h-index 17

Impact in

Papers in

    • Statistical Methods and Inference 17
    • Statistical Methods and Bayesian Inference 16
    • Advanced Statistical Methods and Models 11
    • Spatial and Panel Data Analysis 9
    • Housing Market and Economics 8
    • Economic and Environmental Valuation 5

Eva Cantoni

44 papers receiving 1.4k citations

Peers

Eva Cantoni
Comparison fields: 5 of 150
  • Statistics and Probability 555
  • Statistics, Probability and Uncertainty 143
  • Economics and Econometrics 439
  • Small Animals 83
  • Finance 71
Replace G. K. Robinson with:
G. K. Robinson Australia
Marco Marozzi Italy
A. F. M. Smith United States
Jérôme Saracco France
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Raydonal Ospina Brazil
Fernanda De Bastiani Brazil
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Citations per field
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Citations per year

Countries citing papers authored by Eva Cantoni

Since Specialization
Citations

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

Fields of papers citing papers by Eva Cantoni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001276
2 2007194
3 2010166
4 2009165
5 2006110
6 200665
7 200555
8 200453
9 200247
10 201440
11 201137
12 200629
13 200425
14 201322
15 200619
16 201819
17 201116
18 200813
19 202110
20 20059

About Eva Cantoni

Eva Cantoni is a scholar working on Statistics and Probability, Economics and Econometrics, Global and Planetary Change, Nature and Landscape Conservation and Artificial Intelligence, having authored 46 papers that have together received 1.5k indexed citations. Recurring topics across this work include Statistical Methods and Inference (17 papers), Statistical Methods and Bayesian Inference (16 papers), Advanced Statistical Methods and Models (11 papers), Spatial and Panel Data Analysis (9 papers), Housing Market and Economics (8 papers), Marine and fisheries research (6 papers), Economic and Environmental Valuation (5 papers) and Fish Ecology and Management Studies (5 papers). The work is most often cited by research in Statistics and Probability (555 citations), Statistics, Probability and Uncertainty (143 citations), Economics and Econometrics (439 citations), Small Animals (83 citations) and Finance (71 citations). Eva Cantoni has collaborated with scholars based in Switzerland, United States and Canada. Frequent co-authors include Elvezio Ronchetti, Martin Hoesli, Steven C. Bourassa, Stéphane Héritier, Maria‐Pia Victoria‐Feser, Samuel Copt, Joanna Mills Flemming, Etienne Le Bihan, Jean‐Louis Foulley and William H. Aeberhard. Their work appears in journals such as Computational Statistics & Data Analysis, Statistical Modelling, Canadian Journal of Statistics, Econometrics and Statistics and Scandinavian Journal of Statistics.

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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