Eric Slud

2.2k citations
84 papers · 1.2k indexed · h-index 19

Impact in

Papers in

Eric Slud

78 papers receiving 1.1k citations

Peers

Eric Slud
Comparison fields: 5 of 153
  • Statistics and Probability 585
  • Management Science and Operations Research 167
  • Statistics, Probability and Uncertainty 81
  • Mathematical Physics 90
  • Finance 96
Replace Yi‐Ching Yao with:
Yi‐Ching Yao United States
Calyampudi Radhakrishna Rao United States
Brett Presnell United States
Yasunori Fujikoshi Japan
V. Seshadri Canada
Deborah Nolan United States
John Gurland United States
Grace L. Yang United States
Dean Isaacson United States
James R. Thompson United States
Eric Slud relative to Yi‐Ching Yao United States Yi‐Ching Yao's profile →
Citations per field
00.5×2.8×
Yi‐Ching Yao · 1×
Citations per year

Countries citing papers authored by Eric Slud

Since Specialization
Citations

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

Fields of papers citing papers by Eric Slud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric Slud. 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 Eric Slud. The network helps show where Eric Slud may publish in the future.

Co-authors

The 25 scholars most cited alongside Eric Slud, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Eric Slud Line = papers co-authored together Eric Slud links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1982140
2 201873
3 198471
4 198363
5 198452
6 200642
7 198942
8 198238
9 197738
10 198837
11 201834
12 199334
13 200232
14 197832
15 201729
16 200229
17 202226
18 198125
19 198218
20 198917

About Eric Slud

Eric Slud is a scholar working on Statistics and Probability, Management Science and Operations Research, Economics and Econometrics, Finance and Artificial Intelligence, having authored 84 papers that have together received 1.2k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (28 papers), Statistical Methods and Inference (25 papers), Statistical Methods in Clinical Trials (12 papers), Statistical Distribution Estimation and Applications (11 papers), Stochastic processes and financial applications (7 papers), Stochastic processes and statistical mechanics (7 papers), Advanced Statistical Methods and Models (6 papers) and Insurance, Mortality, Demography, Risk Management (5 papers). The work is most often cited by research in Statistics and Probability (585 citations), Management Science and Operations Research (167 citations), Statistics, Probability and Uncertainty (81 citations), Mathematical Physics (90 citations) and Finance (96 citations). Eric Slud has collaborated with scholars based in United States, Cyprus and Thailand. Frequent co-authors include Lee‐Jen Wei, David P. Byar, Benjamin Kedem, Larry Rubinstein, Sylvan B. Green, Tapabrata Maiti, M. S. Binoj Kumar, Kwame Okrah, Héctor Corrada Bravo and Sridhar Hannenhalli. Their work appears in journals such as Biometrika, Probability Theory and Related Fields, The Annals of Statistics, Advances in Applied Probability and Journal of Statistical Planning and Inference.

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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