Statistician spatio-temporal data analysis and visualization with R, Python and Matlab

PhD Thesis

    Directional Wavelets for Scattered Data and Their Applications

Publications

  1. Jang, D. (2017). Identifying local smoothness for spatially inhomogeneous functions, Computational Statistics, Accepted

  2. Jang, D. (2017). Fusion of Transporation and Spatial Bigdata, The Korea Transport Institute

  3. Jang, D. (2016). Transit User's Tempo-Spatial Pattern Analysis and Simulation with Transportation Databases, The Korea Transport Institute

  4. Jang, D. (2016). Establishing Transport Accessbility in Metropolitan Area, The Korea Transport Institute

  5. Jang, D. (2014). Introduction to GIS data and map manipulation with R, Newsletter - The Korean Statistical Society, October, 2014 , 37-50.

  6. Joo, J. H., Yeon, J. Y. and Jang, D. (2014). Analysis on passenger car travel characteristics by household type, Journal of Korean Society of Transportation, 32, 347-356.

  7. Jang, D., Oh, H.-S. and Kim, D. (2011). Extending the scope of automatic time series model selection: The package autots for R, Communications of the Korean Statistical Society, 18, 319-331.

  8. Jang, D. and Oh, H.-S. (2011). Enhancement of spatially adaptive smoothing splines via parameterization of smoothing parameters, Computational Statistics and Data Analysis, 55, 1029-1040.

  9. Oh, H.-S., Jang, D., Oh, S. and Kim, H. (2010). Improved statistical testing of two-class microarrays with a robust statistical approach, Interdisciplinary BioCentral, 2, 1-6.

  10. Hwang, E., Kwon, Y., Jang, D., Lee J. and Oh, H.-S. (2008). Modeling the trend of apartment market price in Seoul, Communications of the Korean Statistical Society, 15, 173-191.

Papers in progress

  1. Jang, D and Lee, G. (2017). Development of web based seasonal adjusting program with Korean holiday effect.

  2. Jang, D (2017). Finding optiaml traffic counts location with functional thinning

  3. Jang, D. and Hong, D. (2017). Traffic counts estimation on unobserved locations using navigation traffic DB and spatial statistical analysis in large urban area.

  4. Jang, D. and Oh, H.-S. (2017). Estimation of global earthquakes magnitude from scattered observations by a directional wavelet-based method.

  5. Jang, D., Lee, D. and Oh, H.-S.(2017). Weather generation with spatio-temporal correlation in South Korea.

  6. Jang, D., Kim, D. and Oh, H.-S. (2017). SynchWave: The R package for synchrosqueezed wavelet transform.

Contributed talks and posters

  1. November 3, 2012: Directional wavelets for scattered data and their applications, Fall Conference of the Korean Statistical Society, Konkuk University, Seoul, Korea.

  2. May 28, 2011: Dependent structure detection by improved blockwise risk estimation, Spring Conference of the Korean Statistical Society, KAIST, Daejeon, Korea.

  3. December 12, 2010: Dependent structure detection by blockwise risk, 3rd International Conference of the European Research Consortium for Informatics and Mathematics Working Group on Computing & Statistics (ERCIM'10), University of London, London, UK.

  4. August 4, 2009: Extending the scope of automatic time series model selection, Joint Statistical Meetings 2009, Walter E. Washington Convention Center, Washington D. C., USA.

  5. June 29, 2009: Adaptive smoothing using thinning algorithms, 1st Institute of Mathematical Statistics Asia Pacific Rim Meeting (IMS-APRM), Seoul National University, Seoul, Korea.

  6. November 11, 2006: Visualization and pattern analysis of apartment market price in Seoul, Fall Conference of the Korea Business Intelligence Data Mining Society, Dongguk University, Seoul, Korea.

  7. November 4, 2006: Modeling the trend of apartment market price in Seoul, Fall Conference of the Korean Statistical Society, Korea University, Seoul, Korea. (poster)

  8. November 4, 2006: Improved smoothing spline regression by blockwise risk estimation, Fall Conference of the Korean Statistical Society, Korea University, Seoul, Korea. (poster)

Invited talks

  1. October 16, 2014: Smart Mobility and big data in Transportation Planning: KTDB Cases, Department of Geography, Kyung Hee University, Seoul, Korea.

  2. March 29, 2013: Time-frequency & scale analysis and multi-scale wavelets representation for scattered data, Department of Statistics, Inha University, Incheon, Korea.

  3. January 28, 2013: The statistical inference and practice using SPSS, The Research Institute of Nursing Science, Seoul National University, Seoul, Korea.

  4. February 22--24, 2011: The SAS data step and statistical analysis, Department of Industrial Engineering, Konkuk University, Seoul, Korea.

  5. October 15 & 17, 2008: R programming and advanced computing using C and Fortran, Department of Statistics, Yonsei University, Seoul, Korea.

  6. October 8 & 10, 2008: C programming and statistical computing, Department of Statistics, Yonsei University, Seoul, Korea.