Dipak K. Dey
- Statistics and Probability top 0.05%
- Artificial Intelligence top 0.5%
- Statistics, Probability and Uncertainty top 0.2%
- Economics and Econometrics top 1%
- Management Science and Operations Research top 1%
- Co-authors
- Alan E. GelfandMárcia D. BrancoSujit K. SahuKent E. HolsingerPaul O. LewisCidambi SrinivasanMing‐Hui ChenDebajyoti Sinha
- Topics
- Statistical Methods and Bayesian Inference (95 papers)Statistical Distribution Estimation and Applications (70 papers)Statistical Methods and Inference (66 papers)
- Partner nations
- United StatesBrazilUnited Kingdom
In The Last Decade
Dipak K. Dey
228 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 200
- Statistics and Probability 3.6k
- Artificial Intelligence 1.6k
- Statistics, Probability and Uncertainty 748
- Economics and Econometrics 727
- Management Science and Operations Research 607
Countries citing papers authored by Dipak K. Dey
This map shows the geographic impact of Dipak K. Dey'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 Dipak K. Dey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dipak K. Dey more than expected).
Fields of papers citing papers by Dipak K. Dey
This network shows the impact of papers produced by Dipak K. Dey. 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 Dipak K. Dey. The network helps show where Dipak K. Dey may publish in the future.
Co-authorship network of co-authors of Dipak K. Dey
This figure shows the co-authorship network connecting the top 25 collaborators of Dipak K. Dey. A scholar is included among the top collaborators of Dipak K. Dey 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 Dipak K. Dey. Dipak K. Dey 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 | 10 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 28 | |
| 9 | Block Nearest Neighboor Gaussian processes for large datasets | 1 |
| 10 | Reforming Generative Autoencoders via Goodness-of-Fit Hypothesis Testing. | 0 |
| 11 | 9 | |
| 12 | On Clustering Criteria for Smooth Distributions | 0 |
| 13 | 3 | |
| 14 | 0 | |
| 15 | PRIOR AND POSTERIOR PREDICTIVE P-VALUES IN THE ONE-SIDED LOCATION PARAMETER TESTING PROBLEM | 10 |
| 16 | 3 | |
| 17 | 7 | |
| 18 | 14 | |
| 19 | BAYESIAN MODELING OF CORRELATED BINARY RESPONSES VIA SCALE MIXTURE OF MULTIVARIATE NORMAL LINK FUNCTIONS | 45 |
| 20 | 3 |
About Dipak K. Dey
Dipak K. Dey is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence, having authored 243 papers that have together received 6.3k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (95 papers), Statistical Distribution Estimation and Applications (70 papers) and Statistical Methods and Inference (66 papers). The work is most often cited by research in Statistics and Probability (3.6k citations), Statistics, Probability and Uncertainty (748 citations) and Finance (553 citations). Dipak K. Dey has collaborated with scholars based in United States, Brazil and United Kingdom. Frequent co-authors include Alan E. Gelfand, Márcia D. Branco, Sujit K. Sahu, Kent E. Holsinger, Paul O. Lewis, Cidambi Srinivasan, Ming‐Hui Chen, Debajyoti Sinha, Víctor H. Lachos and Bani K. Mallick. Their work appears in journals such as Journal of the American Statistical Association, Analytical Chemistry and Biometrics.
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.