Lynn Kuo

3.8k citations
79 papers · 2.5k indexed · 1 hit paper · h-index 22

Lynn Kuo

73 papers receiving 2.4k citations

Hit Papers

Improving Marginal Likelihood Estimation for Bayesian Phy...7732010202620152020250500750

Peers

Lynn Kuo
Comparison fields: 5 of 174
  • Statistics and Probability 590
  • Software 159
  • Paleontology 282
  • Safety, Risk, Reliability and Quality 181
  • Genetics 483
Replace Simon Wilson with:
Simon Wilson Ireland
John Robinson Australia
Makio Ishiguro Japan
Yoshitaka Sakamoto Japan
G. Kitagawa Japan
David Welch New Zealand
Christian Hennig United Kingdom
S. G. Ghurye United States
Minoo Niknian United States
Uwe Ligges Germany
Lynn Kuo relative to Simon Wilson Ireland Simon Wilson's profile →
Citations per field
00.5×5.3×
Simon Wilson · 1×
Citations per year

Countries citing papers authored by Lynn Kuo

Since Specialization
Citations

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

Fields of papers citing papers by Lynn Kuo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20230
2 20218
3 20212
4 20194
5 20181
6 201725
7 201624
8 201619
9
Dynamic Frailty and Change Point Models for Recurrent Events Data
20131
10 201340
11 201114
12 2009193
13
Detecting differentially expressed genes using calibrated bayes factors
20082
14 200685
15 2005141
16 200167
17 1996114
18 199532
19 199525
20 19892

About Lynn Kuo

Lynn Kuo is a scholar working on Statistics and Probability, Software, Statistics, Probability and Uncertainty, Artificial Intelligence and Management Science and Operations Research, having authored 79 papers that have together received 2.5k indexed citations. Recurring topics across this work include Statistical Methods and Inference (28 papers), Statistical Methods and Bayesian Inference (25 papers), Bayesian Methods and Mixture Models (21 papers), Statistical Distribution Estimation and Applications (15 papers), Genomics and Phylogenetic Studies (6 papers), Gene expression and cancer classification (6 papers), Statistical Methods in Clinical Trials (5 papers) and Reliability and Maintenance Optimization (5 papers). The work is most often cited by research in Statistics and Probability (590 citations), Software (159 citations), Paleontology (282 citations), Safety, Risk, Reliability and Quality (181 citations) and Genetics (483 citations). Lynn Kuo has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Paul O. Lewis, Yu Fan, Wangang Xie, Ming‐Hui Chen, Tae Young Yang, Ming‐Hui Chen, Bani K. Mallick, Alan E. Gelfand, Rui Wu and Charles B. Hall. Their work appears in journals such as Systematic Biology, Journal of the American Statistical Association, Journal of Computational and Graphical Statistics, Biometrical Journal and Computational Statistics & Data Analysis.

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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