Leonardo Rojas‐Nandayapa

457 citations
19 papers · 260 indexed · h-index 7
Topics
Probability and Risk Models (13 papers)Financial Risk and Volatility Modeling (9 papers)Statistical Distribution Estimation and Applications (6 papers)

In The Last Decade

Leonardo Rojas‐Nandayapa

17 papers receiving 250 citations

Peers

Leonardo Rojas‐Nandayapa
Comparison fields: 5 of 73
  • Management Science and Operations Research 123
  • Finance 105
  • Statistics and Probability 70
  • Electrical and Electronic Engineering 37
  • Demography 31
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Qingshuo Song United States
Hans Rudolf Lerche Germany
Łukasz Stettner Poland
Zan-Kan Nie China
Daniel Egloff Switzerland
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Hock Peng Chan Singapore
W.P. Malcolm Australia
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Citations per field
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Citations per year

Countries citing papers authored by Leonardo Rojas‐Nandayapa

Since Specialization
Citations

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

Fields of papers citing papers by Leonardo Rojas‐Nandayapa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leonardo Rojas‐Nandayapa. 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 Leonardo Rojas‐Nandayapa. The network helps show where Leonardo Rojas‐Nandayapa may publish in the future.

Co-authorship network of co-authors of Leonardo Rojas‐Nandayapa

This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo Rojas‐Nandayapa. A scholar is included among the top collaborators of Leonardo Rojas‐Nandayapa 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 Leonardo Rojas‐Nandayapa. Leonardo Rojas‐Nandayapa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 10
2 2
3 6
4 5
5 0
6 3
7 0
8 19
9 62
10 2
11 12
12 5
13 1
14 37
15 6
16 74
17 6
18 1
19 9

About Leonardo Rojas‐Nandayapa

Leonardo Rojas‐Nandayapa is a scholar working on Management Science and Operations Research, Statistics and Probability and Finance, having authored 19 papers that have together received 260 indexed citations. Recurring topics across this work include Probability and Risk Models (13 papers), Financial Risk and Volatility Modeling (9 papers) and Statistical Distribution Estimation and Applications (6 papers). The work is most often cited by research in Finance (105 citations), Management Science and Operations Research (123 citations) and Statistics and Probability (70 citations). Leonardo Rojas‐Nandayapa has collaborated with scholars based in Australia, Denmark and United States. Frequent co-authors include Søren Asmussen, Jens Ledet Jensen, José Blanchet, Sandeep Juneja, Mogens Bladt, Sergey Foss, Dirk P. Kroese, Yoni Nazarathy, Thomas S. Salisbury and Zdravko I. Botev. Their work appears in journals such as Annals of Operations Research, Political Geography and Journal of Applied Probability.

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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