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Lab Introduction : Multiscale Methods in Statistics Lab.

Lab Introduction : Multiscale Methods in Statistics Lab. First Year Graduate Student Seminar May 16, Spring 2016. C ontents. Introduction Lab members Research themes & Activities. I ntroduction. M embers: P rofessor. Hee-Seok Oh

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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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