John Hinde

5.5k citations
68 papers · 3.8k indexed · 1 hit paper · h-index 25

John Hinde

66 papers receiving 3.5k citations

Hit Papers

Statistical Modelling in GLIM6461991202620022014200400600

Peers

John Hinde
Comparison fields: 5 of 206
  • Statistics and Probability 1.1k
  • Insect Science 378
  • Nature and Landscape Conservation 262
  • Management Science and Operations Research 214
  • Statistics, Probability and Uncertainty 118
Replace Nathaniel Schenker with:
Nathaniel Schenker United States
D. Collett United Kingdom
David Firth United Kingdom
Clarice Garcia Borges Demétrio Brazil
Thomas M. Loughin United States
John Haigh United Kingdom
M. Knott United Kingdom
Ming‐Hui Chen United States
José Cirı́aco Pinheiro Brazil
Paul McCullagh United Kingdom
John Hinde relative to Nathaniel Schenker United States Nathaniel Schenker's profile →
Citations per field
00.5×1.6×
Nathaniel Schenker · 1×
Citations per year

Countries citing papers authored by John Hinde

Since Specialization
Citations

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

Fields of papers citing papers by John Hinde

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20230
2 20201
3 202011
4 20192
5 20182
6 20173
7 20164
8 201629
9 20157
10 201124
11 20094
12 200848
13
A new package for fitting random effect models.
20071
14
Linear mean-variance negative binomial models for analysis of orange tissue-culture data
20048
15 200311
16 200071
17 199748
18 199739
19 1993151
20 19881

About John Hinde

John Hinde is a scholar working on Statistics and Probability, Computational Mathematics, Statistics, Probability and Uncertainty, Artificial Intelligence and Management Science and Operations Research, having authored 68 papers that have together received 3.8k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (23 papers), Bayesian Methods and Mixture Models (9 papers), Statistical Methods and Inference (9 papers), Advanced Statistical Methods and Models (7 papers), Economic and Environmental Valuation (5 papers), Statistical Distribution Estimation and Applications (5 papers), Statistical Methods in Clinical Trials (5 papers) and Soil Geostatistics and Mapping (4 papers). The work is most often cited by research in Statistics and Probability (1.1k citations), Insect Science (378 citations), Nature and Landscape Conservation (262 citations), Management Science and Operations Research (214 citations) and Statistics, Probability and Uncertainty (118 citations). John Hinde has collaborated with scholars based in Ireland, United Kingdom and Brazil. Frequent co-authors include Clarice Garcia Borges Demétrio, Murray Aitkin, Dorothy A. Anderson, Brian Francis, M. S. Ridout, Leslie M. Moore, Rafael de Andrade Moral, Deborah J. Anderson, Ross Darnell and Murray Aitken. Their work appears in journals such as Computational Statistics & Data Analysis, Biometrics, Journal of Agricultural Biological and Environmental Statistics, Technometrics and Statistics in Medicine.

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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