Jean‐François Beaumont

417 citations
23 papers · 222 indexed · h-index 9

Jean‐François Beaumont

22 papers receiving 202 citations

Peers

Jean‐François Beaumont
Comparison fields: 5 of 58
  • Statistics and Probability 154
  • Statistics, Probability and Uncertainty 14
  • Nature and Landscape Conservation 17
  • Sociology and Political Science 56
  • Management Science and Operations Research 15
Replace Guillaume Chauvet with:
Guillaume Chauvet France
Jean‐François Dupuy France
Cary T. Isaki United States
Des Raj India
Tereza Neocleous United Kingdom
Xinyi Li China
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Jai Won Choi United States
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Citations per year

Countries citing papers authored by Jean‐François Beaumont

Since Specialization
Citations

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

Fields of papers citing papers by Jean‐François Beaumont

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean‐François Beaumont. 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 Jean‐François Beaumont. The network helps show where Jean‐François Beaumont may publish in the future.

Co-authorship network

The 16 scholars most cited alongside Jean‐François Beaumont, 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 Jean‐François Beaumont Line = papers co-authored together Jean‐François Beaumont links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20230
2 20231
3
QR Prediction for Statistical Data Integration
20221
4 20224
5 20211
6 20192
7 20161
8 20154
9 201415
10 201320
11 20126
12 20118
13
Shadow speaking for real-time closed-captioning of TV broadcasts in french
20102
14 200913
15 200829
16 200736
17 200517
18 20036
19
A Nonresponse Adjustment Strategy using Modeling in the Canadian Labour Force Survey
20031
20 199917

About Jean‐François Beaumont

Jean‐François Beaumont is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Language and Linguistics, having authored 23 papers that have together received 222 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (13 papers), Survey Sampling and Estimation Techniques (10 papers), Survey Methodology and Nonresponse (7 papers), Statistical Methods and Inference (5 papers), Advanced Statistical Process Monitoring (4 papers), Economic and Environmental Valuation (3 papers), Bayesian Methods and Mixture Models (3 papers) and Healthcare Policy and Management (2 papers). The work is most often cited by research in Statistics and Probability (154 citations), Statistics, Probability and Uncertainty (14 citations) and Nature and Landscape Conservation (17 citations). Jean‐François Beaumont has collaborated with scholars based in Canada, France and United States. Frequent co-authors include David Haziza, Anne Ruiz‐Gazen, M. Bernier-Cardou, Chhun-Huor Ung, J. N. K. Rao, Claude Chapdelaine, Patrick Cardinal, Gilles Boulianne, Audrey Béliveau and Julie Brousseau.

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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