Guy P. Nason

88 papers receiving 2.5k citations

Peers

Guy P. Nason
Comparison fields: 5 of 166
  • Computer Vision and Pattern Recognition 948
  • Statistics and Probability 335
  • Applied Mathematics 318
  • Media Technology 265
  • Signal Processing 301
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Brani Vidaković United States
Theofanis Sapatinas Cyprus
Anestis Antoniadis France
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Linda Kaufman United States
Dominique Picard France
Werner Stuetzle United States
Felix Abramovich Israel
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Citations per year

Countries citing papers authored by Guy P. Nason

Since Specialization
Citations

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

Fields of papers citing papers by Guy P. Nason

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guy P. Nason. 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 Guy P. Nason. The network helps show where Guy P. Nason may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 95 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996255
2 2000246
3 2008217
4 1993216
5 1999124
6 1994118
7 200497
8
CRM Proceedings and Lecture Notes
199893
9 200184
10 201369
11 201561
12 200853
13 199951
14
Wavelet regression by cross-validation,
199445
15 200643
16 200242
17 200439
18 199436
19 201433
20 199533

About Guy P. Nason

Guy P. Nason is a scholar working on Computer Vision and Pattern Recognition, Economics and Econometrics, Applied Mathematics, Signal Processing and Artificial Intelligence, having authored 95 papers that have together received 2.7k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (42 papers), Complex Systems and Time Series Analysis (19 papers), Statistical and numerical algorithms (15 papers), Time Series Analysis and Forecasting (12 papers), Spectroscopy and Chemometric Analyses (10 papers), Advanced Image Fusion Techniques (8 papers), Advanced Statistical Methods and Models (5 papers) and Statistical Methods and Inference (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (948 citations), Statistics and Probability (335 citations), Applied Mathematics (318 citations), Media Technology (265 citations) and Signal Processing (301 citations). Guy P. Nason has collaborated with scholars based in United Kingdom, Belgium and United States. Frequent co-authors include Rainer von Sachs, Gerald Kroisandt, David W. Scott, Piotr Fryźlewicz, B. W. Silverman, Bernard W. Silverman, A. Cardinali, Idris A. Eckley, Theofanis Sapatinas and Maarten Jansen. Their work appears in journals such as Statistics and Computing, Journal of the Royal Statistical Society Series B (Statistical Methodology), Journal of the Royal Statistical Society Series A (Statistics in Society), Journal of the Royal Statistical Society Series C (Applied Statistics) and Journal of Statistical Software.

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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