Arjun K. Gupta

7.3k total citations · 2 hit papers
229 papers, 4.1k citations indexed

About

Arjun K. Gupta is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Arjun K. Gupta has authored 229 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 186 papers in Statistics and Probability, 58 papers in Artificial Intelligence and 53 papers in Statistics, Probability and Uncertainty. Recurrent topics in Arjun K. Gupta's work include Statistical Distribution Estimation and Applications (122 papers), Advanced Statistical Methods and Models (67 papers) and Bayesian Methods and Mixture Models (57 papers). Arjun K. Gupta is often cited by papers focused on Statistical Distribution Estimation and Applications (122 papers), Advanced Statistical Methods and Models (67 papers) and Bayesian Methods and Mixture Models (57 papers). Arjun K. Gupta collaborates with scholars based in United States, Colombia and China. Arjun K. Gupta's co-authors include Daya K. Nagar, Jie Chen, Saralees Nadarajah, Graciela González–Farías, Debasis Kundu, Wen‐Jang Huang, Taras Bodnar, Edsel A. Peña, Tamás Varga and John T. Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Technometrics.

In The Last Decade

Arjun K. Gupta

211 papers receiving 3.9k citations

Hit Papers

Design and Analysis of Experiments 2013 2026 2017 2021 2013 2018 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Arjun K. Gupta United States 30 2.1k 809 708 548 493 229 4.1k
R. Douglas Martin United States 23 2.2k 1.0× 995 1.2× 1.4k 2.0× 543 1.0× 449 0.9× 77 5.3k
Ricardo A. Maronna Argentina 23 2.8k 1.3× 1.3k 1.7× 727 1.0× 358 0.7× 268 0.5× 61 4.7k
Kai‐Tai Fang Hong Kong 23 1.1k 0.5× 490 0.6× 503 0.7× 735 1.3× 465 0.9× 90 2.9k
Muni S. Srivastava Canada 33 2.6k 1.2× 573 0.7× 943 1.3× 383 0.7× 232 0.5× 164 4.4k
Govind S. Mudholkar United States 24 2.4k 1.1× 1.5k 1.8× 458 0.6× 298 0.5× 295 0.6× 124 4.3k
Víctor Leiva Chile 46 3.5k 1.6× 1.5k 1.9× 968 1.4× 667 1.2× 541 1.1× 255 5.8k
Daniel Peña Spain 30 1.1k 0.5× 412 0.5× 596 0.8× 392 0.7× 624 1.3× 148 3.4k
Bovas Abraham Canada 24 621 0.3× 550 0.7× 347 0.5× 1.0k 1.9× 287 0.6× 68 2.8k
Tim Bedford United Kingdom 27 562 0.3× 1.2k 1.4× 436 0.6× 490 0.9× 770 1.6× 106 4.2k
R. L. Eubank United States 28 2.4k 1.1× 429 0.5× 695 1.0× 418 0.8× 353 0.7× 84 4.1k

Countries citing papers authored by Arjun K. Gupta

Since Specialization
Citations

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

Fields of papers citing papers by Arjun K. Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arjun K. Gupta. 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 Arjun K. Gupta. The network helps show where Arjun K. Gupta may publish in the future.

Co-authorship network of co-authors of Arjun K. Gupta

This figure shows the co-authorship network connecting the top 25 collaborators of Arjun K. Gupta. A scholar is included among the top collaborators of Arjun K. Gupta 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 Arjun K. Gupta. Arjun K. Gupta 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.
Gupta, Arjun K., et al.. (2017). Student Leave Management System. International journal of advance research and innovative ideas in education. 3(5). 124–131. 3 indexed citations
2.
Gupta, Arjun K., et al.. (2015). Test for the Equality of Partial Correlation Coefficients for Two Populations. Journal of Modern Applied Statistical Methods. 14(1). 70–82.
3.
Nagar, Daya K., et al.. (2013). Properties of the Extended Whittaker Function. 6(2). 70–80. 3 indexed citations
4.
Joarder, Anwar H., et al.. (2013). The Distribution of a Linear Combination of Two Correlated Chi-Square Variables. Revista Colombiana de Estadística. 36(2). 209–219. 6 indexed citations
5.
Gupta, Arjun K. & D. G. Kabe. (2010). A quadratic programming approach to a survey sampling cost minimization problem. DergiPark (Istanbul University). 2 indexed citations
6.
Gupta, Arjun K., et al.. (2010). Convex Ordering of Random Variables and its Applications in Econometrics and Actuarial Science. European Journal of Pure and Applied Mathematics. 3(5). 779–785. 4 indexed citations
7.
Gupta, Arjun K., et al.. (2009). Skewed Double Exponential Distribution and Its Stochastic Representation. European Journal of Pure and Applied Mathematics. 2(1). 1–20. 1 indexed citations
8.
Gupta, Arjun K. & D. G. Kabe. (2008). Selberg-type squared matrices gamma and beta integrals. European Journal of Pure and Applied Mathematics. 1(1). 197–201. 3 indexed citations
9.
Xu, Jin & Arjun K. Gupta. (2007). Asymptotic expansions of the distributions of some test statistics in generalized linear models. Statistics. 41(1). 47–64. 1 indexed citations
10.
Nadarajah, Saralees & Arjun K. Gupta. (2007). Moments and cumulants of the skew normal distribution. Kobe University Repository Kernel (Kobe University). 24. 107–124. 1 indexed citations
11.
Nadarajah, Saralees & Arjun K. Gupta. (2005). On the Moments of the Exponentiated Weibull Distribution. Communication in Statistics- Theory and Methods. 34(2). 253–256. 8 indexed citations
12.
Nadarajah, Saralees & Arjun K. Gupta. (2004). Characterizations of the Beta Distribution. Communication in Statistics- Theory and Methods. 33(12). 2941–2957. 11 indexed citations
13.
Gupta, Arjun K., Thomas Hoover, Il‐Young Jung, et al.. (2002). JAZ volume 73 issue 1 Cover and Front matter. Journal of the Australian Mathematical Society. 73(1). f1–f3. 1 indexed citations
14.
Chen, Jie & Arjun K. Gupta. (2001). ON CHANGE POINT DETECTION AND ESTIMATION. Communications in Statistics - Simulation and Computation. 30(3). 665–697. 66 indexed citations
15.
Gupta, Arjun K., et al.. (2001). IMPROVED MINIMAX ESTIMATOR OF COVARIANCE WHEN ADDITIONAL INFORMATION IS AVAILABLE ON SOME COORDINATES. Communications in Statistics - Simulation and Computation. 30(1). 11–18. 11 indexed citations
16.
Chen, Jie & Arjun K. Gupta. (1997). Testing and Locating Variance Changepoints with Application to Stock Prices. Journal of the American Statistical Association. 92(438). 739–747. 186 indexed citations
17.
Gupta, Arjun K. & Jie Chen. (1996). Detecting changes of mean in multidimensional normal sequences with applications to literature and geology. Computational Statistics. 11(3). 211–221. 19 indexed citations
18.
Gupta, Arjun K., et al.. (1995). On disguised inverted Wishart distribution. Proceedings of the American Mathematical Society. 123(8). 2557–2562. 1 indexed citations
19.
Albert, James H. & Arjun K. Gupta. (1985). Bayesian Methods for Binomial Data with Applications to a Nonresponse Problem. Journal of the American Statistical Association. 80(389). 167–174. 9 indexed citations
20.
Gupta, Arjun K., et al.. (1982). Quadratic Complementary Programming. Journal of the Korean Operations Research and Management Science Society. 7(1). 45–50.

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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