Shipra Banik
- Statistics and Probability top 2%
- Management Science and Operations Research top 10%
- Statistics, Probability and Uncertainty top 5%
- Economics and Econometrics
- Electrical and Electronic Engineering
- Co-authors
- B. M. Golam KibriaParam SilvapulleAhmed N. AlbatinehMahashweta DasMahady HasanMohammad Rejwan Uddin
- Topics
- Stock Market Forecasting Methods (12 papers)Advanced Statistical Methods and Models (9 papers)Statistical Methods and Bayesian Inference (7 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyManagement Science and Operations Research
- Journals
- SHILAP Revista de lepidopterologíaComputational Intelligence and NeuroscienceJournal of Applied Statistics
- Partner nations
- BangladeshUnited StatesIndia
In The Last Decade
Shipra Banik
25 papers receiving 266 citations
Peers
Comparison fields: 5 of 77
- Statistics and Probability 144
- Management Science and Operations Research 66
- Statistics, Probability and Uncertainty 62
- Economics and Econometrics 42
- Electrical and Electronic Engineering 33
Countries citing papers authored by Shipra Banik
This map shows the geographic impact of Shipra Banik'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 Shipra Banik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shipra Banik more than expected).
Fields of papers citing papers by Shipra Banik
This network shows the impact of papers produced by Shipra Banik. 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 Shipra Banik. The network helps show where Shipra Banik may publish in the future.
Co-authorship network of co-authors of Shipra Banik
This figure shows the co-authorship network connecting the top 25 collaborators of Shipra Banik. A scholar is included among the top collaborators of Shipra Banik 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 Shipra Banik. Shipra Banik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 89 | |
| 6 | 8 | |
| 7 | 1 | |
| 8 | 15 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | A simulation study on some confidence intervals for the population standard deviation | 6 |
| 14 | 1 | |
| 15 | 21 | |
| 16 | 7 | |
| 17 | 4 | |
| 18 | 13 | |
| 19 | 17 | |
| 20 | 5 |
About Shipra Banik
Shipra Banik is a scholar working on Statistics and Probability, Management Science and Operations Research and Statistics, Probability and Uncertainty, having authored 32 papers that have together received 289 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (12 papers), Advanced Statistical Methods and Models (9 papers) and Statistical Methods and Bayesian Inference (7 papers). The work is most often cited by research in Statistics and Probability (144 citations), Statistics, Probability and Uncertainty (62 citations) and Management Science and Operations Research (66 citations). Shipra Banik has collaborated with scholars based in Bangladesh, United States and India. Frequent co-authors include B. M. Golam Kibria, Param Silvapulle, Ahmed N. Albatineh, Mahashweta Das, Mahady Hasan and Mohammad Rejwan Uddin. Their work appears in journals such as SHILAP Revista de lepidopterología, Computational Intelligence and Neuroscience and Journal of Applied Statistics.
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.