Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
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).
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
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
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
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
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.