Yaeji Lim

Contact Information

E-mail: yaeji.lim@gmail.com

Department of Applied Statistics,

Chung-Ang University,

Seoul, KOREA


Academic Employment and Education

Mar. 2018 - Present Assistant professor,

Department of Applied Statistics, Chung-Ang University

Mar. 2016 - Feb.2018 Assistant professor,

Department of Statistics, Pukyong National University, Busan, KOREA

Mar. 2015 - Feb.2016 Research Engineer,

Bioinformation Center, Samsung Medical Center

Aug. 2013 - Feb. 2015 Post doctoral,

Department of Statistics, Seoul National University (Advisor: Dr. Hee-Seok Oh)

Mar. 2009 - Aug. 2013 Ph.D. (Statistics) Seoul National University, Seoul, Korea

Mar. 2003 - Feb. 2007 B.A. (Mathematics) POSTECH, Pohang, Korea


Publications

Publications in refereed journals (+: co-first author; ∗: corresponding author)

    1. Y. Lim, H-S. Oh and Y. Kuen (2018). Multiscale Clustering for Functional Data. Journal of Classification. accepted.
    2. Y. Lim, H-S. Oh and Y. Kuen (2018). Functional Clustering of Accelerometer Data via Transformed Input Variables. Journal of the Royal Statistical Society C. In Press.
    3. Park, H., Y. Lim+, Ko, E.S., et. al (2018). Radiomics Signature on Magnetic Resonance Imaging: Association with Disease-Free Survival in Patients with Invasive Breast Cancer. Clinical Cancer Research, pp.clincanres-3783.
    4. Y. Lim (2018). M-estimation of the long-memory parameter by Laplace periodogram. The Korean Data & Information Science Society, 29(2), 523-532.
    5. Y. Lim, Choi, J. S., et. al (2018). Comparative analysis of diagnostic procedures for tumor detection rates in paired data. Statistical methods in medical research, 0962280218763977.
    6. Y. Lim and H-S. Oh (2017). Confidence Intervals for Nonparametric Quantile Regression: An Emphasis on Smoothing Splines Approach. Australian & New Zealand Journal of Statistics, 59(4), 527-543.
    7. Y. Jo and Y. Lim∗, et. al (2017). Principal Component Analysis in the Frequency Domain : a review and their application to climate data. The Korean Journal of Applied Statistics, 30(3), 441-451.
    8. Y. Lim and Eun Sook Ko, et.al (2017). Background parenchymal enhancement on breast MRI: Association with recurrence-free survival in patients with newly diagnosed invasive breast cancer. Breast Cancer Research and Treatment , 163(3), 573–586.
    9. Y. Lim (2017). Principal Component Regression for Spatial Data. The Korean Journal of Applied Statistics, 30(3), 311-321.
    10. J-P Kim, H-S. Oh, and Y. Lim∗(2017). Seasonal Precipitation Prediction via Data-Adaptive Principal Component Regression. International Journal of Climatology, 37(S1), 75-86.
    11. Y. Lim+ and Soo Hoon Kang, et al. (2016). A Model for Predicting the Future Risk of Incident Erosive Esophagitis in an Asymptomatic Healthy Population Undergoing Regular Check-ups. Medicine, 95(4), p.e2591.
    12. Y. Lim and H-S. Oh (2016). Composite quantile periodogram for spectral analysis. Journal of Time Series Analysis, 37, 195–221.
    13. Y. Lim and H-S. Oh (2015). A Data-Adaptive Principal Component Analysis: Use of Composite Asymmetric Huber Function. Journal of Computational and Graphical Statistics, 25(4), 1230-1247.
    14. J-H Kwon, H-S. Oh and Y. Lim∗ (2015). Particulate matter prediction using quantile boosting. The Korean Journal of Applied Statistics, 28(1), 83–92.
    15. Y. Lim and H-S. Oh (2015). Simultaneous confidence Interval for quantile regression. Computational Statistics, 30, 345–358.
    16. Y. Lim, J. Lee, H-S. Oh, and H. Kang (2015). Independent component regression for seasonal climate prediction: An efficient way to improve multimodel ensembles. Theoretical and Applied Climatology, 119(3-4), 433–441.
    17. Y. Lim and H-S. Oh (2014). Variable selection in quantile regression when the models have autoregressive errors. Journal of the Korean Statistical Society, 43, 513–530.
    18. Y. Lim, S. Jo, J. Lee, H-S. Oh, S. Lee, Y. Park and H. Kang (2014). Multimodel Ensemble Forecasting of Rainfall over East Asia: Regularized Regression approach. International Journal of Climatology, 34, 3720–3731.
    19. Y. Lim, Yeonjoo Park and H-S. Oh (2014). Robust principal component analysis by ES- algorithm. Journal of the Korean Statistical Society, 43, 149–159.
    20. Y. Lim, S. Jo, J. Lee, H-S. Oh and H. Kang (2012). An improvement of seasonal climate prediction by regularized canonical correlation analysis. International Journal of Climatology, 32, 1503–1512.
    21. Y. Lim, S. Jo, J. Lee, H-S. Oh and H. Kang (2012). Prediction of East Asian summer precipitation via independent component analysis. Asia-Pacific Journal of Atmospheric Sciences, 48(2), 125–134.
    22. Y. Lim and H-S. Oh (2012). Discussion of time-threshold maps: using information from wavelet reconstructions with all threshold values simultaneously. Journal of the Korean Statistical Society, 41(2), 165-168.
    23. S. Jo, Y. Lim, J. Lee, H-S. Oh and H. Kang (2012). Bayesian regression models for seasonal forecast of precipitation over Korea. Asia-Pacific Journal of Atmospheric Sciences, 48(3), 205–212.
    24. Y. Lim, S. Jo, J. Lee, H-S. Oh and H. Kang (2009). Climate prediction by a hybrid method with emphasizing future precipitation change of East Asia. The Korean Journal of Applied Statistics, 22, 1143–1152.


• Others (+: co-first author)

    1. Nam, Sang Yu and Y. Lim, et al. Preoperative dynamic breast magnetic resonance imaging kinetic features using computer-aided diagnosis: Association with survival outcome and tumor aggressiveness in patients with invasive breast cancer. PloS one 13.4 (2018): e0195756.
    2. Seo Yeon Hahn and Y. Lim, et al. (2017). Role of Ultrasound in Predicting Tumor Invasive- ness in Follicular Variant of Papillary Thyroid Carcinoma. Thyroid, 27(9), 1177-1184.
    3. Y. Lim+ and H. Lee, et. al (2017). Relationship between obesity and development of erosive reflux disease: A mediation analysis of the role of cardiometabolic risk factors. Scientific Reports, 7(1), 6375.
    4. J-K Park and Y. Lim+, et.al (2017). Comparison of anthropometric measurements associated with the risk of endoscopic erosive esophagitis: A cross-sectional study. Obesity Research & Clinical Practice, 11(6), 694-702.
    5. Young Kon Kim and Y. Lim, et al. (2016). Reducing Artifacts during Arterial Phase of Gadoxetate Disodiumanhanced MR Imaging: Dilution Method versus Reduced Injection Rate. Radiology, 283(2), p.160241.
    6. Eun Sook Ko and Y. Lim, et al. (2016). Breast Cancer Heterogeneity: MR Imaging Texture Analysis and Survival Outcomes. Radiology, 282(3), p.160261.
    7. Kang B., and Y. Lim, et al. (2016). Baseline Wall Thickness is Lower in Mucosa Healed Segments 1 Year After Infliximab in Pediatric Crohn’s Disease Patients. Journal of Pediatric Gastroenterology and Nutrition, 64(2), 279–285.
    8. Rihwa Choi and Y. Lim, et.al (2016). A prospective study on serum methylmalonic acid and homocysteine in pregnant women in relation to pregnancy and neonatal outcomes. Nutrients, 8(12) p.797.
    9. Eun Sook Ko and Y. Lim, et al. (2016). Prognostic significance of transverse relaxation rate (R2*) in blood oxygenation level-dependent magnetic resonance imaging in patients with invasive breast cancer. PloS one, 11(7), e0158500.
    10. Eun Sook Ko and Y. Lim, et al. (2016) Analysis of factors influencing the degree of detectability on diffusion-weighted MRI and diffusion background signals in patients with invasive breast cancer, Medicine, 95(27).
    11. Eun Sook Ko and Y. Lim, et al. (2015). Assessment of Invasive Breast Cancer Heterogeneity Using Whole-Tumor Magnetic Resonance Imaging Texture Analysis: Correlations with Pathological Findings. Medicine, 95(3), p.e2453.
    12. Rihwa Choi, H-T. Kim, Y. Lim, M-J. Kim, O. Kwon, K. Jeon, H-Y. Park, B-H. Jeong, W-J. Koh and S-Y Lee (2015). Serum Concentrations of Trace Elements in Patients with Tuberculosis and its Association with Treatment Outcome. Nutrients, 7(7), 5969–5981.