K. V. Mardia

4.5k citations
30 papers · 3.4k indexed · 2 hit papers · h-index 13
Topics
Bayesian Methods and Mixture Models (6 papers)Advanced Statistical Methods and Models (4 papers)Morphological variations and asymmetry (4 papers)

In The Last Decade

K. V. Mardia

29 papers receiving 3.0k citations

Hit Papers

Statistics of Directional Data.19732026199020081973197450010001.5k2.0k

Peers

K. V. Mardia
Comparison fields: 5 of 199
  • Statistics and Probability 609
  • Artificial Intelligence 552
  • Cognitive Neuroscience 441
  • Environmental Engineering 339
  • Geophysics 249
Replace Peter E. Jupp with:
Peter E. Jupp United Kingdom
Geoffrey S. Watson United States
Robert F. Ling United States
David R. Brillinger United States
W. J. Krzanowski United Kingdom
Graham Upton United Kingdom
Chris Fraley United States
Clifford M. Hurvich United States
Alan G. Hawkes United Kingdom
Nicholas Lange United States
K. V. Mardia relative to Peter E. Jupp United Kingdom Peter E. Jupp's profile →
Citations per field
00.5×1.5×
Peter E. Jupp · 1×
Citations per year

Countries citing papers authored by K. V. Mardia

Since Specialization
Citations

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

Fields of papers citing papers by K. V. Mardia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. V. Mardia. 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 K. V. Mardia. The network helps show where K. V. Mardia may publish in the future.

Co-authorship network of co-authors of K. V. Mardia

This figure shows the co-authorship network connecting the top 25 collaborators of K. V. Mardia. A scholar is included among the top collaborators of K. V. Mardia 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 K. V. Mardia. K. V. Mardia 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
#WorkIndexed citations
1
Some Fundamental Properties of Multivariate von Mises Distributions
1
2 1
3 6
4 2
5 28
6 18
7 6
8 12
9 6
10 169
11 11
12 11
13 12
14 3
15 3
16 53
17 31
18
APPLICATIONS OF SOME MEASURES OF MULTIVARIATE SKEWNESS AND KURTOSIS IN TESTING NORMALITY AND ROBUSTNESS STUDIES.breakdown →
621
19
Statistics of Directional Data.breakdown →
2052
20 5

About K. V. Mardia

K. V. Mardia is a scholar working on Statistics and Probability, Geometry and Topology and Artificial Intelligence, having authored 30 papers that have together received 3.4k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (6 papers), Advanced Statistical Methods and Models (4 papers) and Morphological variations and asymmetry (4 papers). The work is most often cited by research in Statistics and Probability (609 citations), Environmental Engineering (339 citations) and Cognitive Neuroscience (441 citations). K. V. Mardia has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include D. V. Gokhale, Peter E. Jupp, J. T. Kent, Tony Greenfield, John Bibby, P. E. Jupp, Terence W. Sutton, Abram Kagan, C. Radhakrishna Rao and R. Bremananth. Their work appears in journals such as Journal of the American Statistical Association, Biometrics and Journal of Applied Physiology.

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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