Guy P. Nason

90 papers receiving 2.5k citations

Peers

Guy P. Nason
Comparison fields: 5 of 170
  • Computer Vision and Pattern Recognition 950
  • Statistics and Probability 332
  • Applied Mathematics 318
  • Media Technology 267
  • Signal Processing 300
Replace Anestis Antoniadis with:
Anestis Antoniadis France
Brani Vidaković United States
Theofanis Sapatinas Cyprus
Linda Kaufman United States
Gérard Kerkyacharian France
Dominique Picard France
Genshiro Kitagawa Japan
Werner Stuetzle United States
Elizaveta Levina United States
Patrice Abry France
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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-authorship network

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
#Work
1 20250
2 20250
3 20231
4 201612
5 20154
6 201125
7 20092
8
A multiscale variance stabilization for binomial sequence proportion estimation
20090
9 200643
10
Simulations and examples for multivariate nonparametric regression using lifting
20044
11
Smoothing the wavelet periodogram using the Haar-Fisz transform
20041
12
Clustering objects on subsets of attributes
200423
13
Multivariate nonparametric regression using lifting
20046
14
Wavelet packet modelling of infant sleep state using heart rate data
200119
15
Some New Methods for Wavelet Density Estimation
20008
16 199730
17
Wavelet shrinkage: asymptopia?
19953
18
Wavelet function estimation using cross-validation
19959
19
Entropy in multivariate analysis: projection pursuit
19925
20 19867

About Guy P. Nason

Guy P. Nason is a scholar working on Computer Vision and Pattern Recognition, Applied Mathematics, Signal Processing, Statistics and Probability and Analytical Chemistry, having authored 97 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 (950 citations), Statistics and Probability (332 citations), Applied Mathematics (318 citations), Media Technology (267 citations) and Signal Processing (300 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, Theofanis Sapatinas, Idris A. Eckley and Maarten Jansen. Their work appears in journals such as Journal of the Royal Statistical Society Series B (Statistical Methodology), Statistics and Computing, Journal of the Royal Statistical Society Series A (Statistics in Society), Journal of Statistical Software and Journal of the Royal Statistical Society Series C (Applied 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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