Rama Shanker

2.1k total citations
148 papers, 1.5k citations indexed

About

Rama Shanker is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Rama Shanker has authored 148 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Statistics and Probability, 45 papers in Statistics, Probability and Uncertainty and 25 papers in Artificial Intelligence. Recurrent topics in Rama Shanker's work include Statistical Distribution Estimation and Applications (113 papers), Probabilistic and Robust Engineering Design (43 papers) and Bayesian Methods and Mixture Models (24 papers). Rama Shanker is often cited by papers focused on Statistical Distribution Estimation and Applications (113 papers), Probabilistic and Robust Engineering Design (43 papers) and Bayesian Methods and Mixture Models (24 papers). Rama Shanker collaborates with scholars based in Eritrea, India and Netherlands. Rama Shanker's co-authors include Ravi Shanker, Kamlesh Kumar Shukla, Suresh Bhalla, Prem Vrat, Ashok Kumar Gupta, Naveet Kaur, Ramakanta Panigrahi, Sanjay Kumar Singh, Varun Singh and Uma Shanker and has published in prestigious journals such as SHILAP Revista de lepidopterología, Inorganic Chemistry and Environmental Science and Pollution Research.

In The Last Decade

Rama Shanker

134 papers receiving 1.3k citations

Peers

Rama Shanker
Rama Shanker
Citations per year, relative to Rama Shanker Rama Shanker (= 1×) peers Amal S. Hassan

Countries citing papers authored by Rama Shanker

Since Specialization
Citations

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

Fields of papers citing papers by Rama Shanker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rama Shanker

This figure shows the co-authorship network connecting the top 25 collaborators of Rama Shanker. A scholar is included among the top collaborators of Rama Shanker 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 Rama Shanker. Rama Shanker 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.
Rastogi, Manoj Kumar, et al.. (2024). Demographic and epidemiological profile of patients with head-and-neck cancer in Bihar, India: A hospital-based retrospective study. Cancer Research Statistics and Treatment. 7(3). 301–307. 2 indexed citations
2.
Shanker, Rama, et al.. (2020). Another Two-Parameter Poisson –Sujatha Distribution. University of Twente Research Information. 10(2). 43–53. 1 indexed citations
3.
Shukla, Kamlesh Kumar & Rama Shanker. (2019). Weighted Ishita Distribution and its Application to Survival data. 20(1). 67–82.
4.
Shanker, Rama, et al.. (2019). Weighted Quasi Akash Distribution:: Properties and Applications. University of Twente Research Information. 9(1). 30–43. 2 indexed citations
5.
Shanker, Rama & Kamlesh Kumar Shukla. (2019). Rama-Kamlesh distribution with properties and Its Applications. 16(4). 11–22.
6.
Shanker, Rama, et al.. (2018). A Size-Biased Poisson-Aradhana Distribution with Applications. University of Twente Research Information. 1 indexed citations
7.
Shanker, Rama, et al.. (2018). A Generalized Poisson-Akash Distribution: Properties and Applications. University of Twente Research Information.
8.
Shanker, Rama, et al.. (2018). A Two-Parameter Poisson-Akash Distribution with Properties and Applications. University of Twente Research Information. 2 indexed citations
9.
Shanker, Rama, et al.. (2017). On Size- Biased Two Parameter Poisson-Lindley Distribution and Its Applications. 7(3). 99–107. 1 indexed citations
10.
Shanker, Rama. (2017). A Size-Biased Poisson-Shanker Distribution and Its Applications. 6(2). 33–44. 3 indexed citations
11.
Shanker, Rama. (2017). Suja Distribution and Its Application. 6(2). 11–19. 3 indexed citations
12.
Shanker, Rama. (2017). Rama Distribution and Its Application. 7(1). 26–35. 19 indexed citations
13.
Shanker, Rama. (2017). A Zero-Truncated Poisson-Shanker Distribution and Its Applications. 7(3). 159–169. 2 indexed citations
14.
Shanker, Rama. (2016). The Discrete Poisson-Sujatha Distribution. 5(1). 1–9. 18 indexed citations
15.
Shanker, Rama. (2016). A Quasi Sujatha Distribution. 5(4). 89–100. 2 indexed citations
16.
Shanker, Rama, et al.. (2016). Size-Biased Poisson-Sujatha Distribution with Applications. 6(4). 145–154. 9 indexed citations
17.
Shanker, Rama, et al.. (2016). A Size-Biased Poisson-Amarendra Distribution and Its Applications. 6(6). 376–385. 3 indexed citations
18.
Shanker, Rama, et al.. (2015). On Size Biased Poisson - Lindley Distribution and Its Applications to Model Thunderstorms. 5(6). 354–360. 4 indexed citations
19.
Shanker, Rama. (2015). Shanker Distribution and Its Applications. 5(6). 338–348. 64 indexed citations
20.
Shanker, Rama, et al.. (2013). On a Size-Biased Quasi Poisson-Lindley Distribution. 2(2). 28–34. 4 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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