Chae Young Lim

635 total citations
58 papers, 439 citations indexed

About

Chae Young Lim is a scholar working on Statistics and Probability, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Chae Young Lim has authored 58 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Statistics and Probability, 11 papers in Economics and Econometrics and 10 papers in Artificial Intelligence. Recurrent topics in Chae Young Lim's work include Spatial and Panel Data Analysis (9 papers), Statistical Methods and Inference (9 papers) and Soil Geostatistics and Mapping (8 papers). Chae Young Lim is often cited by papers focused on Spatial and Panel Data Analysis (9 papers), Statistical Methods and Inference (9 papers) and Soil Geostatistics and Mapping (8 papers). Chae Young Lim collaborates with scholars based in South Korea, United States and Taiwan. Chae Young Lim's co-authors include Mark M. Meerschaert, Tapabrata Maiti, Jongeun Choi, Seungik Baek, Eunpyo Choi, Jungyul Park, Hyung‐Kwan Chang, Taesung Kim, Hamidreza Gharahi and Byron A. Zambrano and has published in prestigious journals such as Journal of the American Statistical Association, The Science of The Total Environment and Technometrics.

In The Last Decade

Chae Young Lim

54 papers receiving 417 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chae Young Lim South Korea 11 68 59 57 55 40 58 439
Éric Matzner-Løber France 12 26 0.4× 47 0.8× 76 1.3× 193 3.5× 51 1.3× 31 769
Roman Hornung Germany 14 38 0.6× 39 0.7× 36 0.6× 105 1.9× 29 0.7× 33 698
Chen Fang China 14 62 0.9× 16 0.3× 13 0.2× 151 2.7× 50 1.3× 46 691
Mehdi Moradi Canada 14 40 0.6× 111 1.9× 87 1.5× 114 2.1× 22 0.6× 46 563
Sara López‐Pintado United States 15 45 0.7× 23 0.4× 74 1.3× 107 1.9× 37 0.9× 33 1.2k
Shaobing Chen China 8 17 0.3× 88 1.5× 39 0.7× 58 1.1× 13 0.3× 12 688
Daniel V. Samarov United States 12 42 0.6× 56 0.9× 16 0.3× 45 0.8× 11 0.3× 30 525
J.M. DeLeo United States 7 24 0.4× 36 0.6× 211 3.7× 108 2.0× 60 1.5× 12 739
Arnab Maity United States 19 70 1.0× 14 0.2× 15 0.3× 133 2.4× 32 0.8× 70 1.2k

Countries citing papers authored by Chae Young Lim

Since Specialization
Citations

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

Fields of papers citing papers by Chae Young Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chae Young Lim. 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 Chae Young Lim. The network helps show where Chae Young Lim may publish in the future.

Co-authorship network of co-authors of Chae Young Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Chae Young Lim. A scholar is included among the top collaborators of Chae Young Lim 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 Chae Young Lim. Chae Young Lim 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.
Lim, Chae Young, et al.. (2024). Spatial regression with multiplicative errors, and its application with LiDAR measurements. Journal of the Korean Statistical Society. 53(4). 1177–1204. 2 indexed citations
2.
Lim, Chae Young. (2024). Spatial Statistics for Data Science: Theory and Practice with R.,. Journal of the American Statistical Association. 119(548). 3186–3187. 5 indexed citations
3.
Lee, Hee‐Seung, et al.. (2023). Corrective feedback guides human perceptual decision-making by informing about the world state rather than rewarding its choice. PLoS Biology. 21(11). e3002373–e3002373. 2 indexed citations
4.
Lim, Chae Young, Jongeun Choi, Ahmed Ramadan, et al.. (2022). Regularized nonlinear regression for simultaneously selecting and estimating key model parameters: Application to head-neck position tracking. Engineering Applications of Artificial Intelligence. 113. 104974–104974. 4 indexed citations
5.
Chakraborty, Sounak, et al.. (2022). A Spatiotemporal Analytical Outlook of the Exposure to Air Pollution and COVID-19 Mortality in the USA. Journal of Agricultural Biological and Environmental Statistics. 27(3). 419–439. 4 indexed citations
6.
Zambrano, Byron A., Hamidreza Gharahi, Chae Young Lim, Whal Lee, & Seungik Baek. (2021). Association of vortical structures and hemodynamic parameters for regional thrombus accumulation in abdominal aortic aneurysms. International Journal for Numerical Methods in Biomedical Engineering. 38(2). e3555–e3555. 13 indexed citations
7.
Zhang, Liangliang, Byron A. Zambrano, Jongeun Choi, et al.. (2020). Intraluminal thrombus effect on the progression of abdominal aortic aneurysms by using a multistate continuous-time Markov chain model. Journal of International Medical Research. 48(11). 1220768001–1220768001. 4 indexed citations
8.
Lim, Chae Young, et al.. (2018). Model selection using mass-nonlocal prior. Statistics & Probability Letters. 147. 36–44. 1 indexed citations
9.
Lim, Chae Young, et al.. (2018). Bayesian model selection for generalized linear models using non-local priors. Computational Statistics & Data Analysis. 133. 285–296. 5 indexed citations
10.
Dey, Tanujit, Kun Ho Kim, & Chae Young Lim. (2018). Bayesian time series regression with nonparametric modeling of autocorrelation. Computational Statistics. 33(4). 1715–1731. 2 indexed citations
11.
Lim, Chae Young, Song Yi Park, Kyung Hye Park, Ha Young Park, & Ji Eun Kim. (2018). The predictive factors for hospitalization of nonurgent patients visiting an emergency department in an urban area: a single center study. Journal of the Korean society of emergency medicine. 29(2). 152–159. 1 indexed citations
12.
Paul, Rajib, et al.. (2017). Assessing the association of diabetes self-management education centers with age-adjusted diabetes rates across U.S.: Aspatial cluster analysis approach. Spatial and Spatio-temporal Epidemiology. 24. 53–62. 2 indexed citations
13.
Lim, Chae Young, et al.. (2016). Latent Class Analysis on Adolescents’ School Violence Victimization Types. 24(3). 177–200. 1 indexed citations
14.
Lim, Chae Young, et al.. (2013). Parameter estimation for operator scaling random fields. Journal of Multivariate Analysis. 123. 172–183. 6 indexed citations
15.
Lim, Chae Young, et al.. (2012). Tail estimation of the spectral density for a stationary Gaussian random field. Journal of Multivariate Analysis. 116. 74–91. 7 indexed citations
16.
Lim, Chae Young, et al.. (2010). The Effects of Violence Perception on Dating Violence, and the Moderating Effects of Relationship Satisfaction. Journal of community welfare. 147–179. 1 indexed citations
17.
Yoon, Jin Ho, et al.. (2008). The Effect of Intensive Therapy Using Nebulized Antibiotics after Endoscpic Sinus Surgery. Korean Journal of Otorhinolaryngology-head and Neck Surgery. 51(7). 623–629.
18.
Lim, Chae Young & Michael L. Stein. (2008). Properties of spatial cross-periodograms using fixed-domain asymptotics. Journal of Multivariate Analysis. 99(9). 1962–1984. 9 indexed citations
19.
Guo, Hongwen, Chae Young Lim, & Mark M. Meerschaert. (2008). Local Whittle estimator for anisotropic random fields. Journal of Multivariate Analysis. 100(5). 993–1028. 22 indexed citations
20.
Lee, Young Mi, et al.. (2005). A case of adrenal gland dependent hyperadrenocorticism with mitotane therapy in a Yorkshire terrier dog. Journal of Veterinary Science. 6(4). 363–363.

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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