Oscar Ngesa

574 citations
43 papers · 348 indexed · h-index 11
Topics
Statistical Distribution Estimation and Applications (17 papers)Statistical Methods and Bayesian Inference (12 papers)Statistical Methods and Inference (11 papers)

In The Last Decade

Oscar Ngesa

42 papers receiving 335 citations

Peers

Oscar Ngesa
Comparison fields: 5 of 86
  • Statistics and Probability 137
  • Nutrition and Dietetics 67
  • Hematology 65
  • Statistics, Probability and Uncertainty 56
  • Epidemiology 36
Replace Enayetur Raheem with:
Enayetur Raheem Bangladesh
Van Zyl South Africa
X. Joan Hu Canada
Carlo Federici Italy
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Nicolas Savy France
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Jane Mwangi Kenya
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Oscar Ngesa relative to Enayetur Raheem Bangladesh Enayetur Raheem's profile →
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Citations per year

Countries citing papers authored by Oscar Ngesa

Since Specialization
Citations

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

Fields of papers citing papers by Oscar Ngesa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Oscar Ngesa. 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 Oscar Ngesa. The network helps show where Oscar Ngesa may publish in the future.

Co-authorship network of co-authors of Oscar Ngesa

This figure shows the co-authorship network connecting the top 25 collaborators of Oscar Ngesa. A scholar is included among the top collaborators of Oscar Ngesa 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 Oscar Ngesa. Oscar Ngesa 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 2
2 1
3 6
4 4
5 10
6 12
7 23
8 18
9 1
10 13
11 1
12 4
13
Exponentiated Generalized Transformed-Transformer Family of Distributions
9
14 4
15 1
16 8
17
A flexible random effects distribution in disease mapping models
3
18 20
19 24
20 75

About Oscar Ngesa

Oscar Ngesa is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Modeling and Simulation, having authored 43 papers that have together received 348 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (17 papers), Statistical Methods and Bayesian Inference (12 papers) and Statistical Methods and Inference (11 papers). The work is most often cited by research in Statistics and Probability (137 citations), Statistics, Probability and Uncertainty (56 citations) and Hematology (65 citations). Oscar Ngesa has collaborated with scholars based in Kenya, Pakistan and South Africa. Frequent co-authors include Henry Mwambi, Samuel Mwalili, Abdisalam Hassan Muse, Suleman Nasiru, Thomas Achia, Quarraisha Abdool Karim, Huda M. Alshanbari, Christophe Chesneau, Saad J. Almalki and Gamal A. Abd-Elmougod. Their work appears in journals such as PLoS ONE, Scientific Reports and International Journal of Environmental Research and Public Health.

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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