Peter E. Jupp

7.2k total citations · 3 hit papers
60 papers, 4.6k citations indexed

About

Peter E. Jupp is a scholar working on Artificial Intelligence, Statistics and Probability and Geometry and Topology. According to data from OpenAlex, Peter E. Jupp has authored 60 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 20 papers in Statistics and Probability and 12 papers in Geometry and Topology. Recurrent topics in Peter E. Jupp's work include Advanced Statistical Methods and Models (12 papers), Bayesian Methods and Mixture Models (11 papers) and Morphological variations and asymmetry (10 papers). Peter E. Jupp is often cited by papers focused on Advanced Statistical Methods and Models (12 papers), Bayesian Methods and Mixture Models (11 papers) and Morphological variations and asymmetry (10 papers). Peter E. Jupp collaborates with scholars based in United Kingdom, Denmark and New Zealand. Peter E. Jupp's co-authors include Kanti V. Mardia, M. Tribus, R. D. Levine, T. Lewis, B. J. J. Embleton, N. I. Fisher, John T. Kent, Ole E. Barndorff–Nielsen, K. V. Mardia and René Thom and has published in prestigious journals such as Journal of the American Chemical Society, The Journal of Chemical Physics and Journal of the American Statistical Association.

In The Last Decade

Peter E. Jupp

58 papers receiving 4.3k citations

Hit Papers

Directional Statistics 1979 2026 1994 2010 1999 1988 1979 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Peter E. Jupp United Kingdom 17 1.0k 566 461 439 421 60 4.6k
K. V. Mardia United Kingdom 13 552 0.5× 609 1.1× 339 0.7× 218 0.5× 441 1.0× 30 3.4k
Jesper Möller Denmark 32 1.1k 1.1× 1.1k 1.9× 747 1.6× 485 1.1× 112 0.3× 160 5.2k
David R. Brillinger United States 44 1.7k 1.6× 1.7k 3.0× 484 1.0× 437 1.0× 1.7k 4.0× 189 13.4k
Harvey Gould United States 26 761 0.7× 266 0.5× 515 1.1× 913 2.1× 298 0.7× 98 12.0k
Geoffrey S. Watson United States 21 829 0.8× 1.2k 2.0× 405 0.9× 709 1.6× 912 2.2× 50 7.7k
B. B. Mandelbrot United States 24 1.2k 1.2× 168 0.3× 982 2.1× 900 2.1× 463 1.1× 47 14.1k
Dietrich Stoyan Germany 40 833 0.8× 1.3k 2.4× 1.1k 2.5× 482 1.1× 82 0.2× 290 10.9k
T. Teichmann United States 25 735 0.7× 388 0.7× 284 0.6× 433 1.0× 333 0.8× 54 13.2k
Wilfrid S. Kendall United Kingdom 22 472 0.5× 520 0.9× 293 0.6× 159 0.4× 92 0.2× 105 3.6k
John W. Van Ness United States 15 579 0.6× 610 1.1× 293 0.6× 482 1.1× 245 0.6× 37 6.4k

Countries citing papers authored by Peter E. Jupp

Since Specialization
Citations

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

Fields of papers citing papers by Peter E. Jupp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter E. Jupp. 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 Peter E. Jupp. The network helps show where Peter E. Jupp may publish in the future.

Co-authorship network of co-authors of Peter E. Jupp

This figure shows the co-authorship network connecting the top 25 collaborators of Peter E. Jupp. A scholar is included among the top collaborators of Peter E. Jupp based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peter E. Jupp. Peter E. Jupp is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Arnold, Richard, Peter E. Jupp, & Helmut Schaeben. (2023). Orientation relationships, orientational variants and the embedding approach. Journal of Applied Crystallography. 56(3). 725–736. 1 indexed citations
2.
Jupp, Peter E.. (2023). A parameterisation-invariant modification of the score test. St Andrews Research Repository (St Andrews Research Repository). 7(S1). 429–439.
3.
Healy, David & Peter E. Jupp. (2018). Bimodal or quadrimodal? Statistical tests for the shape of fault patterns. Solid Earth. 9(4). 1051–1060. 4 indexed citations
4.
Arnold, Richard, Peter E. Jupp, & Helmut Schaeben. (2017). Statistics of ambiguous rotations. Journal of Multivariate Analysis. 165. 73–85. 5 indexed citations
5.
Jupp, Peter E.. (2015). Copulae on products of compact Riemannian manifolds. Journal of Multivariate Analysis. 140. 92–98. 3 indexed citations
6.
Fewster, Rachel M. & Peter E. Jupp. (2013). Information on parameters of interest decreases under transformations. Journal of Multivariate Analysis. 120. 34–39. 4 indexed citations
7.
Bachmann, Florian, Ralf Hielscher, Peter E. Jupp, et al.. (2010). Inferential statistics of electron backscatter diffraction data from within individual crystalline grains. Journal of Applied Crystallography. 43(6). 1338–1355. 105 indexed citations
8.
Borchers, David L., Tiago A. Marques, Þorvaldur Gunnlaugsson, & Peter E. Jupp. (2010). Estimating Distance Sampling Detection Functions When Distances Are Measured With Errors. Journal of Agricultural Biological and Environmental Statistics. 15(3). 346–361. 34 indexed citations
9.
Fewster, Rachel M., S. T. Buckland, Kenneth P. Burnham, et al.. (2008). Estimating the Encounter Rate Variance in Distance Sampling. Biometrics. 65(1). 225–236. 123 indexed citations
10.
Stone, James V. & Peter E. Jupp. (2006). Free-Lunch Learning: Modeling Spontaneous Recovery of Memory. Neural Computation. 19(1). 194–217. 2 indexed citations
11.
Jupp, Peter E., et al.. (2004). Improved likelihood ratio and score tests on concentration parameters of von Mises–Fisher distributions. Statistics & Probability Letters. 72(2). 93–102. 7 indexed citations
12.
Chikuse, Yasuko & Peter E. Jupp. (2003). A test of uniformity on shape spaces. Journal of Multivariate Analysis. 88(1). 163–176. 7 indexed citations
13.
Barndorff–Nielsen, Ole E., Richard D. Gill, & Peter E. Jupp. (2001). On quantum statistical interference. IMA Journal of Numerical Analysis. 2001024(3). 203–4. 2 indexed citations
14.
Jupp, Peter E., et al.. (1998). Precision in Estimating the Frequency Separation between Spectral Lines. Journal of Magnetic Resonance. 135(1). 23–29. 4 indexed citations
15.
Jupp, Peter E.. (1992). Derivative strings, differential strings and semi-holonomic jets. Proceedings of the Royal Society of London Series A Mathematical and Physical Sciences. 436(1896). 89–98. 2 indexed citations
16.
Barndorff–Nielsen, Ole E., et al.. (1992). Finite-dimensional algebraic representations of the infinite phylon group. Acta Applicandae Mathematicae. 28(3). 219–252. 3 indexed citations
17.
Barndorff–Nielsen, Ole E. & Peter E. Jupp. (1989). Approximating exponential models. Annals of the Institute of Statistical Mathematics. 41(2). 247–267. 8 indexed citations
18.
Jupp, Peter E. & K. V. Mardia. (1982). A Characterization of the Multivariate Pareto Distribution. The Annals of Statistics. 10(3). 12 indexed citations
19.
Jupp, Peter E. & Kanti V. Mardia. (1981). Amendments and Corrections: `A General Correlation Coefficient for Direction Data and Related Regression Problems'. Biometrika. 68(3). 738–738. 1 indexed citations
20.
Jupp, Peter E. & Kanti V. Mardia. (1980). A general correlation coefficient for directional data and related regression problems. Biometrika. 67(1). 163–173. 78 indexed citations

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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