The H-Function : Theory and Applications
Impact in
Classified as
- Journal
- Medical Entomology and Zoology
In The Last Decade
doi.org/w33609275 →Countries where authors are citing The H-Function : Theory and Applications
This map shows the geographic impact of The H-Function : Theory and Applications. 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 The H-Function : Theory and Applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The H-Function : Theory and Applications more than expected).
Fields of papers citing The H-Function : Theory and Applications
This network shows the impact of The H-Function : Theory and Applications. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The H-Function : Theory and Applications.
About The H-Function : Theory and Applications
This paper, published in 2010, received 684 indexed citations . Written by A. M. Mathai, Rajendra K. Saxena and H. J. Haubold covering the research area of Numerical Analysis, Mathematical Physics and Statistical and Nonlinear Physics. It is primarily cited by scholars working on Electrical and Electronic Engineering (313 citations), Modeling and Simulation (204 citations), Applied Mathematics (140 citations), Computer Networks and Communications (136 citations) and Statistical and Nonlinear Physics (107 citations). Published in Medical Entomology and Zoology.
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.
This paper is also available at doi.org/w33609275.