Keying Ye

1.9k citations
68 papers · 1.2k · h-index 20

Impact in

Papers in

Keying Ye

61 papers receiving 1.2k citations

Peers

Keying Ye
Comparison fields: 5 of 158
  • Statistics and Probability 309
  • Statistics, Probability and Uncertainty 105
  • Management Science and Operations Research 135
  • Equine 18
  • Signal Processing 68
Replace Eric Ziegel with:
Eric Ziegel
David J. Jenkinson United Kingdom
Samuel Müller Australia
Ian Durbach South Africa
Tim Verdonck Belgium
Prem K. Goel United States
Nicola Torelli Italy
Justin Bleich United States
Hans Riedwyl Switzerland
Kimberly F. Sellers United States
Keying Ye relative to Eric Ziegel Eric Ziegel's profile →
Citations per field
00.5×10×15×21.8×
Eric Ziegel · 1×
Citations per year

Countries citing papers authored by Keying Ye

Since Specialization
Citations

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

Fields of papers citing papers by Keying Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Keying Ye, 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 Keying Ye Line = papers co-authored together Keying Ye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003140
2 2005112
3 2007101
4 201494
5 200362
6 201359
7 199749
8 200045
9 202145
10 200235
11 199931
12 201028
13 200528
14 199527
15 199127
16 200426
17
Probabilidad y estadística para ingeniería y ciencias
201225
18 201424
19 199423
20 200620

About Keying Ye

Keying Ye is a scholar working on Statistics and Probability, Management Science and Operations Research, Artificial Intelligence, Statistics, Probability and Uncertainty and Computational Theory and Mathematics, having authored 68 papers that have together received 1.2k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (19 papers), Optimal Experimental Design Methods (14 papers), Advanced Statistical Methods and Models (12 papers), Bayesian Methods and Mixture Models (10 papers), Statistical Methods and Inference (8 papers), Statistical Methods in Clinical Trials (8 papers), Advanced Statistical Process Monitoring (6 papers) and Water Quality and Resources Studies (6 papers). The work is most often cited by research in Statistics and Probability (309 citations), Statistics, Probability and Uncertainty (105 citations), Management Science and Operations Research (135 citations), Equine (18 citations) and Signal Processing (68 citations). Keying Ye has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Eric P. Smith, Mingjin Yan, Wei Sha, Pedro Mendes, Dongchu Sun, Edward F. Fern, Zhenxin Zhan, Shouhuai Xu, Chenting Su and Li Xu. Their work appears in journals such as Journal of the American Statistical Association, Journal of Statistical Planning and Inference, Journal of Statistical Computation and Simulation, Environmental and Ecological Statistics and Environmetrics.

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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