Sangyeol Lee

3.5k citations
220 papers · 2.4k indexed · h-index 27

Sangyeol Lee

203 papers receiving 2.2k citations

Peers

Sangyeol Lee
Comparison fields: 5 of 125
  • Statistics and Probability 1.2k
  • Finance 1.2k
  • Statistics, Probability and Uncertainty 336
  • General Economics, Econometrics and Finance 391
  • Economics and Econometrics 606
Replace Fabienne Comte with:
Fabienne Comte France
Denis Bosq France
Winfried Stute Germany
I. V. Basawa United States
Alexander Aue United States
Xiaofeng Shao United States
Hira L. Koul United States
Liudas Giraitis United Kingdom
Marie Hušková Czechia
Jeffrey D. Hart United States
Sangyeol Lee relative to Fabienne Comte France Fabienne Comte's profile →
Citations per field
00.5×4.3×
Fabienne Comte · 1×
Citations per year

Countries citing papers authored by Sangyeol Lee

Since Specialization
Citations

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

Fields of papers citing papers by Sangyeol Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20240
4 20241
5 20241
6 20211
7 20212
8 202110
9 202017
10
Simulation of blended vision and monovision with multifocal intraocular lenses by image fusion
20191
11
Cusum of squares test for discretely observed sample from diusion processesy
20101
12
Credibility estimation via kernel mixed effects model
20090
13 20091
14
Jarque-Bera Normality Test for the Driving Levy Process of a Discretely Observed Univariate SDE
20089
15
Modelling KOSPI200 Data Based on GARCH(1,1) Parameter Change Test
20073
16 20068
17 20035
18 20022
19 200182
20 200052

About Sangyeol Lee

Sangyeol Lee is a scholar working on Statistics and Probability, Finance and Statistics, Probability and Uncertainty, having authored 220 papers that have together received 2.4k indexed citations. Recurring topics across this work include Financial Risk and Volatility Modeling (128 papers), Statistical Methods and Inference (84 papers), Advanced Statistical Methods and Models (51 papers), Statistical Distribution Estimation and Applications (41 papers), Market Dynamics and Volatility (35 papers), Monetary Policy and Economic Impact (35 papers), Advanced Statistical Process Monitoring (32 papers) and Stochastic processes and financial applications (20 papers). The work is most often cited by research in Statistics and Probability (1.2k citations), Finance (1.2k citations) and Statistics, Probability and Uncertainty (336 citations). Sangyeol Lee has collaborated with scholars based in South Korea, Taiwan and United States. Frequent co-authors include Cathy W. S. Chen, Okyoung Na, Young‐Mi Lee, Jeongcheol Ha, Byungsoo Kim, Alex Karagrigoriou, Zuowei Shen, Wayne Lawton, Jungsik Noh and Masanobu Taniguchi. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Mathematics of Computation.

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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