2024

Kang, S. and Oh, H.-S. (2024). Spherical random projection. Journal of the Royal Statistical Society, Series B. Accepted for publication. 

Kang, S. and Oh, H.-S. (2024). Probabilistic principal curves on Riemannian manifolds. IEEE Transactions on Pattern Analysis and Machine Intelligence. Accepted for publication. 

Kang, S. and Oh, H.-S. (2024). Novel sampling method for the von Mises-Fisher distribution. Statistics and Computing. https://doi.org/10.1007/s11222-024-10419-3 

Kim, J., Oh, H.-S. and Cho, H. (2024). Moving sum procedure for change point detection under piecewise linearity. Technometrics. https://doi.org/10.1080/00401706.2024.2308202 

Song, W., Oh, H.-S., Cheung, K. and Lim, Y. (2024). Multi-feature clustering of step data using multivariate functional principal component analysis. Statistical Papers. https://doi.org/10.1007/s00362-023-01467-4

Kim, K. and Oh, H.-S. (2024). Network time series forecasting using spectral graph wavelet transform. International Journal of Forecasting. https://doi.org/10.1016/j.ijforecast.2023.08.006

Choi, G. and Oh, H.-S. (2024). Decomposition via elastic-band transform. Pattern Recognition Letters, 182, 76-82.  

Kim, S., Kwon, Y., Kim, J., Bae, K. and Oh, H.-S. (2024).  A model averaging prediction of two-way functional data in semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing, 37(1), 76-86.  

Park, Y., Oh, H.-S. and Lim, Y. (2024). A data-adaptive dimension reduction for functional data via penalized low-rank approximation. Statistics and Computing, 34, 36. 

Kang, S. and Oh, H.-S. (2024). Forecasting South Korea's presidential election via multiparty dynamic Bayesian modeling. International Journal of Forecasting, 40, 124-141.

2023

Park, S., Oh, H.-S. and Lee, J. (2023). Lévy adaptive B-spline regression via overcomplete systems. Statistica Sinica. 33, 2715-2737.

Kim, M., Oh, H.-S. and Lim, Y. (2023). Zero-inflated time-series clustering via ensemble thick-pen transform. Journal of Classification, 40, 407-431.

Lee, J. and Oh, H.-S. (2023). Robust spherical principal curves. Pattern Recognition, 138, 109380.

Kim, K., Oh, H.-S. and Park, M. (2023). Principal component analysis for river network data: Use of spatio-temporal correlation and heterogeneous covariance structure. Environmetrics, 34, e2753.   

Choi, G. and Oh, H.-S. (2023). Elastic-band transform for visualization and detection. Pattern Recognition Letters, 166, 119-125.

2022

Oh, H.-S., Choi, G. and Kim, D. (2022). Decomp2d: An R solution for image decomposition. SoftwareX, 19, 101182.  

Lee, J., Kim, J. and  Oh, H.-S. (2022). spherepc: An R package for dimension reduction on a sphere. The R Journal, 14, 167-181.   

Park, S. and Oh, H.-S. (2022). Lifting scheme for streamflow data in river networks. Journal of the Royal Statistical Society, Series C, 71, 467-490. 

Shin, H. and Oh, H.-S. (2022). Robust geodesic regression. International Journal of Computer Vision, 130, 478-503. 

Lim, Y. and Oh, H.-S. (2022). Quantile spectral analysis of long-memory processes. Empirical Economics, 62, 1245-1266. 

2021

Lim, Y., Kwon, J. and Oh, H.-S. (2021). Principal component analysis in the wavelet domain. Pattern Recognition, 119, Article 108096. 

Lee, J., Kim, J. and Oh, H.-S. (2021). Spherical principal curves. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43, 2165-2171. 

Kim, D., Oh, H.-S. and Choi, G. (2021). EPT: An R package for ensemble patch transform. SoftwareX, 14, 100704.   

Jang, J.-Y.,  Oh, H.-S., Lim, Y.  and Cheung, K. (2021). Ensemble clustering for step data via binning. Biometrics, 77, 293-304.  

Lim, Y. and Oh, H.-S.  (2021). Robust coherence analysis for long-memory processes. Applied Economics Letters, 28, 335-342.  

Kim, J., Park, S., Kwon, J., Lim, Y. and Oh, H.-S. (2021). Estimation of spatio-temporal extreme distribution using a quantile factor model. Extremes, 24, 177-195. 

2020

Lim, Y., Cheung, K. and Oh, H.-S. (2020). A generalization of functional clustering for discrete multivariate longitudinal data. Statistical Methods in Medical Research, 29, 3205-3217. 

Kim, J. and Oh, H.-S. (2020). Pseudo-quantile functional data clustering. Journal of Multivariate Analysis, 178, 104626. 

Kwon, J., Oh, H.-S.  and Lim, Y. (2020). Dynamic principal component analysis with missing values. Journal of Applied Statistics, 47, 1957-1969. 

Kim, D., Choi, G. and Oh, H.-S. (2020). Ensemble patch transformation: A flexible framework for decomposition and filtering of signal. EURASIP Journal on Advances in Signal Processing, 30 (2020). https://doi.org/10.1186/s13634-020-00690-7. 

Oh, H.-S. and Kim, D. (2020). Image decomposition by bidimensional ensemble patch transform. Pattern Recognition Letters, 135, 173-179.  

2019

Lim, Y., Oh, H.-S.  and Cheung, K. (2019). Multiscale clustering for functional data. Journal of Classification, 36, 368-391.

Lim, Y., Oh, H.-S.  and Cheung, K. (2019). Functional clustering of accelerometer data via transformed input variables. Journal of the Royal Statistical Society, Series C, 68, 495-520.

2018

Park, S., Kwon, J., Kim, J. and Oh, H.-S. (2018). Prediction of extremal precipitation: use of quantile regression forests.  Extremes, 21, 436-476. 

Kwon, J., Heo, T.,  Kim, J. K. and Oh, H.-S. (2018).  A new P-wave detector via moving empirical cumulative distribution function.  Bulletin of the Seismological Society of America, 108, 2080-2089. 

Choi, G., Kim, D. and Oh, H.-S. (2018).  Enhancement of variational mode decomposition with missing values. Signal Processing, 142, 75-86. 

2017

Lim, Y. and Oh, H.-S. (2017). Confidence intervals for nonparametric quantile regression: an emphasis on smoothing splines approach.  Australian & New Zealand Journal of Statistics, 527-543. 

Kim, J., Lim, Y., Kang, H.-S. and Oh, H.-S. (2017). Seasonal precipitation prediction via data-adaptive principal component regression. International Journal of Climatology, 37, 75-86.

Park, S. and Oh, H.-S. (2017). Spatio-temporal analysis of particulate matter extremes in Seoul : Use of multiscale approach. Stochastic Environmental Research and Risk Assessment, 31, 2401–2414.

Jang, D., Naveau, P. and Oh, H.-S. (2017). Identifying local smoothness for spatially inhomogeneous functions.  Computational Statistics, 32, 1115-1138.

2016

Kim, D. and Oh, H.-S. (2016). Empirical mode decomposition with missing values. SpringerPlus, 5:2016, DOI 10.1186/s40064-016-3692-1. 

Lim, Y. and Oh, H.-S. (2016). A data-adaptive principal component analysis: Use of composite asymmetric Huber function. Journal of Computational and Graphical Statistics, 25, 1230-1247.

Kim, D. and Oh, H.-S. (2016). Intrinsic pattern preserving boundary treatment method for empirical mode decomposition. Advances in Data Science and Adaptive Analysis, 08, No. 02, 1650008. 

Chen, Y. and Oh, H.-S. (2016). Spectrum measurement modelling and prediction based on wavelets. IET Communications, 10, 2192-2198.

Chen, Y. and Oh, H.-S. (2016). A survey of measurement-based spectrum occupancy modeling for cognitive radios. IEEE Communications Surveys and Tutorials, 18, 848-859.

Lim, Y. and Oh, H.-S. (2016). Composite quantile periodogram for spectral analysis. Journal of Time Series Analysis, 37, 195-221. 

2015

Choi, G., Lee, Y., Kim, D., Yu, K. and Oh, H.-S. (2015). Variational mode decomposition with missing data. The Korean Journal of Applied Statistics, 28, 159-174.

Kim, G., Lee, J., Kim, Y. and Oh, H.-S. (2015). Sparse Bayesian representation in time-frequency domain. Journal of Statistical Planning and Inference, 166, 126-137.

Shin, D.-H., Lee, J. W., Park, J.-E., Choi, I.-Y., Kim, H. J., Oh, H.-S. and Kim, H. (2015). Multiple genes related to muscle identified through a joint analysis of a two-stage genome-wide association study for racing performance of 1,156 Thoroughbreds. Asian-Australasian Journal of Animal Sciences, 28, 771-781.

Park, M. S., Kim, D. and Oh, H.-S. (2015). Quantile-based empirical mode decomposition: An efficient way to decompose noisy signals. IEEE Transactions on Instrumentation & Measurement, 64, 1802-1813.

Lim, Y. and Oh, H.-S. (2015). Simultaneous confidence interval for quantile regression. Computational Statistics, 30, 345-358.

Lim, Y., Lee, J., Kang, H.-S. and Oh, H.-S. (2015). Independent component regression for seasonal climate prediction: an efficient way to improve multimodel ensembles. Theoretical and Applied Climatology, 119, 433-441.

Kwon, J., Lim, Y. and Oh, H.-S. (2015). Particulate matter prediction using quantile boosting. The Korean Journal of Applied Statistics, 28, 83-92.

Park, M. S.,  Kim, D. and Oh, H.-S. (2015). Signal reconstruction by synchrosqueezed wavelet transform. Communications for Statistical Applications and Methods, 22, 159-172. 

2014

Park, M. S., Kim, T.-H. , Cho, E.-S. , Kim, H. and Oh, H.-S. (2014).  Genomic selection for adjacent genetic markers of Yorkshire pigs using regularized regression approaches. Asian-Australasian Journal of Animal Sciences, 27, 1678-1683. 

Park, M. S., Kim, T.-H. , Cho, E.-S. , Kim, H. and Oh, H.-S. (2014). A comparative study of regularized regression approaches using R: Application to SNP and litter size of Yorkshire pigs. Journal of Agriculture and Life Science, 48, 147-155. 

Lim, Y. and Oh, H.-S. (2014). Variable selection in quantile regression when the models have autoregressive errors. Journal of the Korean Statistical Society, 43, 513-530. 

Lim, Y., Park, Y. and Oh, H.-S. (2014). Robust principal component analysis via ES-algorithm. Journal of the Korean Statistical Society, 43, 149-159.

Lim, Y., Jo, S., Lee, J., Lee, S.-G., Park, Y., Kang, H.-S. and Oh, H.-S. (2014). Multimodel ensemble forecasting of rainfall over East Asia: regularized regression approach. International Journal of Climatology, 34, 3720-3731.

Lee, Y. and Oh, H.-S. (2014). A new sparse variable selection via random-effect model. Journal of Multivariate Analysis, 125, 89-99. 

2013

Park, M., Cho, S. and Oh, H.-S. (2013). The role of functional data analysis for instantaneous frequency estimation. Computational Statistics, 28, 1965-1987.

Park, M., Kim, D., Cho, S. and Oh, H.-S. (2013). Functional data classification of variable stars. Communications for Statistical Applications and Methods, 20, 271-281.

Park, M. S., Kim, D. and Oh, H.-S. (2013). Empirical mode decomposition using the second derivative. The Korean Journal of Applied Statistics, 26, 335-347.

Park, M., Kim, D. and Oh, H.-S. (2013). Classification of variable stars using thick-pen transform method. Publications of the Astronomical Society of the Pacific, 125, 470-476.

Lee, J. and Oh, H.-S. (2013). Bayesian regression based on principal components for high-dimensional data. Journal of Multivariate Analysis, 117, 175-192.

Park, W., Oh, H.-S. and Kim, H. (2013). Acceleration of X-chromosome gene order evolution in the cattle lineage. BMB Reports, 46, 310-315.

2012

Kim, D., Kim, K. and Oh, H.-S. (2012). Extending the scope of empirical mode decomposition by smoothing. EURASIP Journal on Advances in Signal Processing, 1, 168.

Jo, S., Lim, Y., Oh, H.-S., Lee, J. and Kang, H.-S. (2012). Bayesian regression models for seasonal forecast of precipitation over Korea. Asia-Pacific Journal of Atmospheric Sciences, 48, 205-212.

Lim, Y., Jo, S., Oh, H.-S., Lee, J. and Kang, H.-S. (2012). Prediction of East Asian summer precipitation via independent component analysis. Asia-Pacific Journal of Atmospheric Sciences, 48, 125-134.

Lim, Y., Jo, S., Oh, H.-S., Lee, J. and Kang, H.-S. (2012). An improvement of seasonal climate prediction by regularized canonical correlation analysis. International Journal of Climatology, 32, 1503-1512.

Kim, D., Park, M. and Oh, H.-S. (2012).  Bidimensional statistical empirical mode decomposition. IEEE Signal Processing Letters, 19, 191-194.

Lee, D., Lee, J., Oh, H.-S. and Lee, Y. (2012)  Future weather generation with spatio-temporal correlation for the four major river basins in South Korea. The Korean Journal of Applied Statistics, 25, 351-362.

Lim, Y. and Oh, H.-S. (2012). Discussion of Time-Threshold Maps: using information from wavelet reconstructions with all threshold values simultaneously.  Journal of the Korean Statistical Society, 41, 165-168. 

2011

Shen, S. S., Gurung, A., Easterling, D., Oh, H.-S. and T. Shu (2011). The 20th century contiguous US temperature changes indicated by daily data and higher statistical moments. Climatic Change, 109, 287-317.

Park, M., Kim, D. and Oh, H.-S. (2011). A reinterpretation of EMD by cubic spline interpolation. Advances in Adaptive Data Analysis, 3, 527-540.

Fryzlewicz, P. and Oh, H.-S. (2011). Thick-pen transform for time series. Journal of the Royal Statistical Society B, 73, 499-529. 

Kim, D., Naveau, P. and Oh, H.-S. (2011). Hybrid wavelet denoising procedure of discontinuous surfaces. IET Image Processing, 5, 684-692.

Oh, H.-S., Nychka, D. and Lee, T. C. M. (2011). Fast nonparametric quantile regression with arbitrary smoothing method. Journal of Computational and Graphical Statistics, 20, 510-526.

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

Park, J.-E., Lee, J., Oh, H.-S. and Kim, H. (2011). Principal components analysis applied to genetic evaluation of racing performance of Thoroughbred race horses in Korea. Livestock Science, 135, 293-299.

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.

2010

Lee, J., Lee, J. W., Oh, H.-S. and Kim, H. (2010). Prediction models for racing performance of domestic progeny of Throughbred. Journal of Animal Science and Technology, 52, 459-466.

Lee, J., Lee, Y. and Oh, H.-S. (2010). Long-term forecasting by wavelet-based filter bank selections and its applicationn. The Korean Journal of Applied Statistics, 23, 249-261.

Lee, D., An, H., Lee, J., Oh, H.-S. and Lee, H.-S. (2010). Improved multisite stochastic weather generation with applications to historical data in South Korea. Asia-Pacific Journal of Atmospheric Sciences, 46, 497-504.

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

2009

Lim, Y., Jo, S., Oh, H.-S., Lee, J. and Kang, H.-S. (2009). Climate prediction by a hybrid method with emphasizing future precipitation change of East Asia. The Korean Journal of Applied Statistics, 22, 1143-1152.

Kim, D. and Oh, H.-S. (2009). EMD: A package for empirical mode decomposition and Hilbert spectrum. The R Journal, 1, 40-46.

Kim, D., Suh, J. and Oh, H.-S. (2009). A multi-resolution approach to non-stationary financial time series using the Hilbert-Huang transform. The Korean Journal of Applied Statistics, 22, 499-513.

Kim, D., Lee, Y. and Oh, H.-S. (2009). Cross-validated wavelet shrinkage. Computational Statistics, 24, 197-512.

Kim, D., Kim, Y. and Oh, H.-S. (2009). Robust wavelet shrinkage using robust selection of thresholds. Statistics and Computing, 19, 27-34.

2008

Kim, Y., Choi, H. and Oh, H.-S. (2008). Smoothly clipped absolute deviation on high dimensions. Journal of the American Statistical Association, 103, 1665-1673.

Kim, D., Lee, Y. and Oh, H.-S. (2008). A fast wavelet approach for recovering damaged images. Journal of Applied Statistics, 35, 927-938.

Kim, D., Peak, S. H. and Oh, H.-S. (2008). A Hilbert-Huang transform approach for predicting cyber-attacks. Journal of Korean Statistical Society, 37, 277-283.

Kim, H.-M. and Oh, H.-S. (2008). Bayesian automatic polynomial wavelet regression. Journal of Statistical Planning and Inference, 138, 2303-2312.

Park, C. G., Lee, H. and Oh, H.-S. (2008). Bayesian selection of primary resolution and wavelet basis functions for wavelet regression. Computational and Statistics, 23, 291-302.

Lee, J. and Oh, H.-S. (2008). Circular statistics in musicology. Communications of The Korean Statistical Society, 15, 273-282.

Hwang, E., Kwon, Y., Jang, D., Oh, H.-S. and Lee, J. (2008). Modeling the trend of apartment market price in Seoul. Communications of The Korean Statistical Society, 15, 173-192.

Kim, K. O. and Oh, H.-S. (2008). Reliability functions estimated from commonly used yield models. Microelectronics Reliability, 48, 481-489.

Lee, J., Kim, D. and Oh, H.-S. (2008). A recipe for robust estimation using pseudo data. Journal of Korean Statistical Society, 37, 63-72. 

2007

Oh, H.-S., Nychka, D. and Lee, T. C. M. (2007). The role of pseudo data for robust smoothing with application to wavelet regression. Biometrika, 94, 893-904.

Oh, H.-S. and Kim, D.  (2007). SpherWave: R package for analyzing scattered spherical data by spherical wavelets. R News, 7, 2-7. 

Kim, D. and Oh, H.-S. (2007). Network design and preprocessing for multi-scale spherical basis function representation. Journal of Korean Statistical Society, 36, 209-228.

Oh, H.-S. and Lee, T. C. M. (2007).  Robust penalized regression spline fitting with application to additive mixed modeling. Computational Statistics, 22, 159-171.

2006

Kim, D. and Oh, H.-S. (2006). Hierarchical smoothing by empirical mode decomposition. The Korean Journal of Applied Statistics, 19, 319-329.

Lim, D., Oh, H.-S. and Kim, H. (2006).  Theoretical peptide mass distribution in the non-redundant protein database of the NCBI. Genomics & Informatics, 4, 51-56.

Kim, D., Oh, H.-S. and Lee, Y. (2006).  Hierarchical-likelihood-based wavelet method for denoising signals with missing data. IEEE Signal Processing Letters, 13, 361-364.

Kim, D. and Oh, H.-S. (2006). Discussion on Double hierarchical generalized linear models by Y. Lee and J. Nelder. Journal of the Royal Statistical Society C, 55, 176-177.

Kim, D. and Oh, H.-S. (2006). CVThresh: R package for level-dependent cross-validation thresholding. Journal of Statistical Software, 5, 1-13.

2005

Oh, H.-S. and Lee, T. C. M. (2005). Hybrid wavelet shrinkage: a method for boundary correction. Computational Statistics and Data Analysis, 48, 809-819.

Oh, H.-S. (2005). Spherical wavelets and their application to meteorological data. Geostatistics Banff, 819-831. 

2004

Oh, H.-S. and Lee, T. C. M. (2004). Automatic polynomial wavelet regression. Statistics and Computing, 14, 337-341.

Naveau, P. and Oh, H.-S. (2004).  Polynomial wavelet regression for images with irregular boundaries. IEEE Transactions on Image Processing, 13, 773-781.

Oh, H.-S., Nychka, D., Brown, T. and Charbonneau, P. (2004). Period analysis of variable stars by robust smoothing. Journal of the Royal Statistical Society C, 53, 15-30.

Oh, H.-S. and Li, T.-H. (2004). Estimation of global temperature fields from scattered observations by a spherical-wavelet-based spatially adaptive method. Journal of the Royal Statistical Society B, 66, 221-238.

2003

Oh, H.-S., Ammann, C., Naveau, P., Nychka, D. and Otto-Bliesner, B. (2003). Multi-resolution time series analysis applied to solar irradiance and climate reconstructions. Journal of Atmospheric and Solar-Terrestrial Physics, 65, 191-201.

Naveau, P., Ammann, C. and Oh, H.-S. (2003). An automatic statistical methodology to extract pulse-like forcing factors in climatic time series: Application to volcanic events.  Volcanism and the Earth's Atmosphere, Geophysical Monograph, 139, 177-186.

2002

Li, T.-H. and Oh, H.-S. (2002). Wavelet spectrum and its characterization property for random processes. IEEE Transactions on Information Theory, 48, 2922-2937.

2001

Oh, H.-S., Naveau, P. and Lee, G. (2001). Polynomial boundary treatment for wavelet regression. Biometrika, 88, 291-298.