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Lab Introduction : Multiscale Methods in Statistics Lab.

Dive into the world of multiscale methods in statistics with insights on research interests, selected publications, lab members, and current projects. Discover research themes like spatio-temporal multiscale transform, robust PCA, and extreme PM10 prediction.

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Lab Introduction : Multiscale Methods in Statistics Lab.

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  1. Lab Introduction:Multiscale Methods in Statistics Lab. First Year Graduate Student Seminar May 16, Spring 2016

  2. Contents • Introduction • Lab members • Research themes & Activities

  3. Introduction

  4. Members: Professor • Hee-Seok Oh • Research interests: multiscale methods in statistics, function estimation, time series, statistical climatology • Selected publications • Composite quantile periodogramfor spectral analysis • Quantile-based empirical mode decomposition • Thick-pen transform for time series • The role of pseudo data for robust smoothing with application to wavelet regression • Estimation of global temperature fields from scattered observations by a spherical wavelet based spatially adaptive method

  5. Members: Students

  6. Members: Current students • 3 Ph.D. course students • Guebin Choi, Seoncheol Park, Youjung Jo • 4 M.S. course students • HyejinYoo, Junhyeon Kwon, Jung-Eum Kim, Miyeon Kim

  7. Members: Alumni • 5 past Ph.D. course students • University (1), Statistics Korea (1), Research institute (2), Post Doc. (1) • 13 past M.S. course students • Study abroad (3),Public enterprises(4),Research institute (1),Industry (5)

  8. Research themes • Multiscale transform • Asymmetric norm problem • Application problem

  9. Research themes • Multiscale transform • Directional wavelet transform for scattered data • Elastic-band transform • Thick-pen transform • Spatio-temporal multiscale transform

  10. Research themes • Directional wavelet transform for scattered data (Hee-Seok Oh)

  11. Research themes • Elastic Band(Guebin Choi)

  12. Research themes • Spatio-temporal multiscale transform(Seoncheol Park)

  13. Research themes • Asymmetric norm problem • Data-adaptive PCA • Unified framework for robust PCA • Composite quantile periodogram • Robust PCA in frequency domain • Data-adaptive factor analysis

  14. Research themes • Robust PCA(Jung-EumKim)

  15. Research themes • Data-adaptive factor analysis (Junhyeon Kwon)

  16. Research themes • Application problem • Seasonal climate prediction • Extreme PM10 prediction • Multiscale functional clustering

  17. Research themes • Extreme PM10 prediction (Seoncheol Park)

  18. Activities

  19. Contact information • Lab location 25-401 & 437 • Guebin Choi gbchoi0914@gmail.com • Seoncheol Park pscstat@gmail.com • Youjung Jo jyj0702@snu.ac.kr • HyejinYoopoplady@naver.com • Junhyeon Kwon junhyeonkwon@gmail.com • Jung-Eum Kim snukingdom@gmail.com • Miyeon Kim miyeon3110@nate.com

  20. Thank You 감사합니다

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