Subhash C. Narula

2.0k total citations
86 papers, 1.3k citations indexed

About

Subhash C. Narula is a scholar working on Statistics and Probability, Management Science and Operations Research and Control and Systems Engineering. According to data from OpenAlex, Subhash C. Narula has authored 86 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Statistics and Probability, 28 papers in Management Science and Operations Research and 23 papers in Control and Systems Engineering. Recurrent topics in Subhash C. Narula's work include Advanced Statistical Methods and Models (33 papers), Multi-Criteria Decision Making (14 papers) and Optimization and Mathematical Programming (14 papers). Subhash C. Narula is often cited by papers focused on Advanced Statistical Methods and Models (33 papers), Multi-Criteria Decision Making (14 papers) and Optimization and Mathematical Programming (14 papers). Subhash C. Narula collaborates with scholars based in United States, Brazil and Sweden. Subhash C. Narula's co-authors include John F. Wellington, Vassil Vassilev, Pekka Korhonen, Mitchell Harwitz, Kenneth J. Levy, Heinz Roland Weistroffer, Carmen Diva Saldiva de André, M. M. Desu, Brian Boffey and V. A. Sposito and has published in prestigious journals such as Technometrics, European Journal of Operational Research and Statistics in Medicine.

In The Last Decade

Subhash C. Narula

85 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Subhash C. Narula United States 19 360 309 301 187 177 86 1.3k
Han-Lin Li Taiwan 19 84 0.2× 369 1.2× 275 0.9× 120 0.6× 424 2.4× 63 1.5k
Cécile Murat France 12 85 0.2× 421 1.4× 228 0.8× 93 0.5× 310 1.8× 30 1.1k
Richard E. Wendell United States 19 47 0.1× 256 0.8× 166 0.6× 221 1.2× 261 1.5× 39 958
A. Kaufmann 5 590 1.6× 1.2k 3.9× 147 0.5× 57 0.3× 506 2.9× 7 2.0k
James P. Ignizio United States 21 125 0.3× 750 2.4× 392 1.3× 50 0.3× 995 5.6× 76 1.9k
Patrick Meyer France 15 150 0.4× 539 1.7× 243 0.8× 31 0.2× 168 0.9× 67 1.4k
A. Hadi‐Vencheh Iran 27 186 0.5× 1.3k 4.4× 256 0.9× 46 0.2× 430 2.4× 100 2.1k
G. Hadley United States 11 135 0.4× 576 1.9× 694 2.3× 26 0.1× 382 2.2× 22 2.8k
Shaojian Qu China 23 111 0.3× 523 1.7× 131 0.4× 81 0.4× 262 1.5× 127 1.7k
V.S.S. Yadavalli South Africa 19 125 0.3× 150 0.5× 170 0.6× 60 0.3× 73 0.4× 115 1.0k

Countries citing papers authored by Subhash C. Narula

Since Specialization
Citations

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

Fields of papers citing papers by Subhash C. Narula

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Subhash C. Narula. 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 Subhash C. Narula. The network helps show where Subhash C. Narula may publish in the future.

Co-authorship network of co-authors of Subhash C. Narula

This figure shows the co-authorship network connecting the top 25 collaborators of Subhash C. Narula. A scholar is included among the top collaborators of Subhash C. Narula 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 Subhash C. Narula. Subhash C. Narula 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.
André, Carmen Diva Saldiva de, et al.. (2003). An overview of the variables selection methods for the minimum sum of absolute errors regression. Statistics in Medicine. 22(13). 2101–2111. 6 indexed citations
2.
Vassilev, Vassil, et al.. (2001). An Interactive Reference Direction Algorithm For Solving Multi‐Objective Convex Nonlinear Integer Programming Problems. International Transactions in Operational Research. 8(4). 367–380. 9 indexed citations
3.
André, Carmen Diva Saldiva de, et al.. (2000). Coefficients of determinations for variable selection in the msae regression. Communication in Statistics- Theory and Methods. 29(3). 623–642. 6 indexed citations
4.
André, Carmen Diva Saldiva de, et al.. (2000). Influence measure for the L 1 regression. Communication in Statistics- Theory and Methods. 29(4). 837–849. 11 indexed citations
5.
Weistroffer, Heinz Roland & Subhash C. Narula. (1997). The state of multiple criteria decision support software. Annals of Operations Research. 72(0). 299–313. 13 indexed citations
6.
Narula, Subhash C., et al.. (1993). Bootstrap confidence intervals for the minimum sum of absolute errors regression. Journal of Statistical Computation and Simulation. 48(3-4). 127–133. 4 indexed citations
7.
Narula, Subhash C., V. A. Sposito, & James E. Gentle. (1991). Comparison of computer programs for simple linear L 1 regression. Journal of Statistical Computation and Simulation. 39(1-2). 63–68. 3 indexed citations
8.
André, Carmen Diva Saldiva de, Carlos A. Peres, & Subhash C. Narula. (1991). An iterative procedure for the estimation of parameters in a dose-response model. Communications in Statistics - Simulation and Computation. 20(2-3). 763–775. 1 indexed citations
9.
Narula, Subhash C., et al.. (1989). Perturbation analysis for the minimum sum of absolute errors regression. Communications in Statistics - Simulation and Computation. 18(3). 957–970. 1 indexed citations
10.
Korhonen, Pekka, Subhash C. Narula, & Jyrki Wallenius. (1989). An evolutionary approach to decision-making, with an application to media selection. Mathematical and Computer Modelling. 12(10-11). 1239–1244. 9 indexed citations
11.
Gehring, Hermann & Subhash C. Narula. (1986). Project cost planning with qualitative information. International Journal of Project Management. 4(2). 61–65. 5 indexed citations
12.
Morettin, Pedro A., et al.. (1985). Statistics in Latin America. The American Statistician. 39(4). 274–278. 2 indexed citations
13.
Wellington, John F. & Subhash C. Narula. (1984). An algorithm for regression quantiles. Communications in Statistics - Simulation and Computation. 13(5). 683–704. 6 indexed citations
14.
Narula, Subhash C. & John F. Wellington. (1983). Selection of variables in linear regression: a pragmatic approach. Journal of Statistical Computation and Simulation. 17(3). 159–172. 7 indexed citations
15.
Narula, Subhash C. & John F. Wellington. (1982). The Minimum Sum of Absolute Errors Regression: A State of the Art Survey. International Statistical Review. 50(3). 317–317. 124 indexed citations
16.
Harwitz, Mitchell, et al.. (1981). Spatial Choice in Consumer Behavior: Towards a Contextual Theory of Demand. Economic Geography. 57(4). 362–362. 31 indexed citations
17.
Narula, Subhash C., et al.. (1980). Degree-constrained minimum spanning tree. Computers & Operations Research. 7(4). 239–249. 131 indexed citations
18.
Narula, Subhash C., et al.. (1977). Approximations to the chi-square distribution. Journal of Statistical Computation and Simulation. 5(4). 267–277. 2 indexed citations
19.
Narula, Subhash C. & M. M. Desu. (1976). Algorithm AS 101: Distribution-Free Confidence Intervals. Journal of the Royal Statistical Society Series C (Applied Statistics). 25(3). 309–309. 1 indexed citations
20.
Narula, Subhash C., et al.. (1975). Sample Size Calculations in Exponential Life Testing. Technometrics. 17(2). 229–231. 10 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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