..........Journal Articles..........
 Q.V. Nong and C.T. Ng(2021), Clustering of subsample means based on pairwise L1 regularized empirical likelihood, Annals of the Institute of Statistical Mathematics, 73, 135174.
 C.T. Ng, W. Lee, and Y. Lee (2020), In defense of LASSO, Communications in Statistics  Theory and Methods.
 C.T. Ng, Y. Shi, and N.H. Chan (2020), Markowitz portfolio and the blur of history, International Journal of Theoretical and Applied Finance, 23, (5), 2050030.
 J.Park, C.T. Ng, and M.H. Na (2020), Empirical likelihood method for longitudinal data generated from unequallyspaced Lèvy processes, Journal of Korean Statistical Society, 49, (3), 10081025.
 K.Zhang, C.T. Ng, Y.M. Kwon, and M.H. Na (2020+), New concepts of principal component analysis based on maximum separation of clusters, Communications in Statistics  Simulation and Computation.
 K. Zhang, C.T. Ng, and M.H. Na (2020) Real time prediction of irregular periodic time series data, Journal of Forecasting, 39, 501–511.
 S. Jeong, J. Ko, M. Kang, J. Yeom, C.T. Ng, S. Lee, Y. Lee, and H. Kim (2020) Geographical variations in gross primary production and evapotranspiration of paddy rice in the Korean Peninsula, Science of the Total Environment, 714, 136632 1–23
 V.C. Nguyen and C.T. Ng (2020). Variable selection under multicollinearity using modified log penalty, to appear in Journal of Applied Statistics. 47, 201–230
 C.T. Ng, W. Lee, and Y. Lee (2020) Logical and Test Consistency in Pairwise Multiple Comparisons, Journal of Statistical Planning and Inference, 206, 145–162
 K. Zhang and C.T. Ng (2020). Adaptive LASSO regression against heteroscedastic idiosyncratic factors in the covariates , Statistics and Its Interface, 13, 65–75
 V.C. Nguyen, S. Jeong, J. Ko, C.T. Ng, and J. Yeom (2019). Mathematical Integration of RemotelySensed Information into a Crop Modelling Process for Mapping Crop Productivity, Remote Sensing, 11, 2131, 117.
 V.C. Nguyen and C.T. Ng (2019). Removing the singularity of a penalty via thresholding function matching, Journal of Korean Statistical Society, 48, 613–635
 Y. Shi, C.T. Ng, Z. Feng, C.K.F. Yiu (2019). A descent algorithm for constrained LAD Lasso estimation with applications in portfolio selection, Journal of Applied Statistics, 46, 1988–2009
 Q.V. Nong, C.T. Ng, W. Lee, and Y. Lee (2019). Hypothesis Testing via a penalizedlikelihood approach, Journal of Korean Statistical Society, 48, 265–277
 C.T. Ng, J. Ko, J. Yeom, S. Jeong, G. Jeong (2019). Delineation of rice productivity projected via integration of a crop model with geostationary satellite imagery in North Korea, Korean Journal of Remote Sensing, 35, 57–81
 J. Ko, C.T. Ng, S. Jeong, J. Kim, B. Lee, and H. Kim (2019). Impacts of regional climate change on barley yield and its geographical variation in South Korea, International Agrophysics, 33, 91–96.
 J. Yeom, S. Jeong, G. Jeong, C.T. Ng, R.C. Deo, and J. Ko (2018). Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMIrice model, Scientific Reports, 8, 161211–1612115
 Y. Shi, C.T. Ng, and C.K.F. Yiu (2018). Portfolio selection based on asymmetric Laplace distribution, coherent risk measure, and expectationmaximization estimation, Quantitative Finance and Economics, 2, 776–797.
 K. Zhang, C.T. Ng, and M. Na (2018). Computational explosion in the frequency estimation of sinusoidal data, Communications for Statistical Applications and Methods, 25, 431–442.
 M. Noh, Y. Ok, M. Na, and C.T. Ng (2018). Analysis of degradation data using double hierarchical generalized linear model, Journal of the Korean Data and Information Science Society, 29, 217–228.
 J. Choi, J. Ko, C.T. Ng, S. Jeong, J. Tenhunen, W. Xue, and J. Cho (2018). Quantification of CO2 fluxes in paddy rice based on the characterization and simulation of CO2 assimilation approaches, Agricultural and Forest Meteorology. 249, 348–366
 C.T. Ng, W. Lee, and Y. Lee (2018). Changepoint Estimators with True Identification Property, Bernoulli. 24(1), 616–660
 C.T. Ng, C. Li, and X. Fan (2017). A fast algorithm for reconstructing multiple sequence alignment and phylogeny simultaneously, Current Bioinformatics. 12, 329–348
 C.T. Ng and C.Y. Yau (2017). Information criterion of seriously overfitting changepoint models, Statistics and Its Interface, 10, 343–353
 Y. Choi, C.T. Ng, and J. Lim (2017). Regularized LRT for Large Scale Covariance Matrices: One Sample Problem, Journal of Statistical Planning and Inference, 180, 108–123
 C.T. Ng, S. Oh, and Y. Lee (2016). Going beyond oracle property: Selection consistency and uniqueness of local solution of the generalized linear model, Statistical Methodology, 32, 147–160
 C.T. Ng and H. Joe (2016). Comparison of nonnested models under a general measure of distance, Journal of Statistical Planning and Inference, 170, 166–185
 Y. Liu, N.H. Chan, C.T. Ng, and P.S. Wong (2016). Shrinkage estimation of meanvariance portfolio, International Journal of Theoretical and Applied Finance, 19, 16500031–165000325
 C.T. Ng and N.H. Chan (2015). Stochastic integral convergence: A white noise calculus approach, Electronic Journal of Statistics, 9, 2035–2057
 C.T. Ng, C.Y. Yau, and N.H. Chan (2015). Likelihood inferences for highdimensional factor analysis of time series with applications in finance, Journal of Computational and Graphical Statistics, 24, 866884
 W. Son, C.T. Ng, and J. Lim (2015). A new integral representation of the coverage probability of a random convex hull, Communications for Statistical Applications and Methods, 22, 69–80.
 C.T. Ng and C.W. Yu (2014). Modified SCAD penalty for constrained variable selection problems, Statistical Methodology, 21, 109–134.
 C.T. Ng, J. Lim, K. Lee, D. Yu, and S. Choi (2014). A fast algorithm to sample the number of vertexes and the area of the random convex hull on the unit square. Computational Statistics, 29, 1187–1205.
 C.T. Ng and H. Joe (2014). Model Comparison with Composite Likelihood Information Criteria. Bernoulli, 20, 1738–1764.
 N.H. Chan and C.T. Ng (2011). A note on asymptotic inference for FIGARCH(p,d,q) models, Statistics and its Inference, 4, 227–233.
 S. Lee and C.T. Ng (2011). Normality test for multivariate conditional heteroskedastic dynamic regression models, Economics Letters, 111 (1), 75–77.
 C.T. Ng., H. Joe, D. Karlis, and J. Liu (2011). Composite likelihood for time series models with a latent autoregressive process, Statistica Sinica, 21, 279–305.
 C.T., Ng, J. Lim, and H. Kyu (2011). Testing stochastic orders in tails of contingency tables, Journal of Applied Statistics, 38 (6), 1133–1149.
 H. Joe and C.T. Ng. (2010). Generating random AR(p) and MA(q) Toeplitz correlation matrices. Journal of Multivariate Analysis, 101 (6), 1532–1545.
 S. Lee and C.T. Ng. (2010). Trimmed portmanteau test for linear process with infinite variance. Journal of Multivariate Analysis, 101 (4), 984–998.
 N.H. Chan and C.T. Ng. (2009). Asymptotic inference for nonstationary GARCH(p,q) models. Electronic Journal of Statistics, 3, 956–992.
 N.H. Chan and C.T. Ng (2009). Stochastic integrals driven by fractional Brownian motion and arbitrage, A Tale of Two Integrals. Quantitative Finance, 519–525.
 N.H. Chan and C.T. Ng (2006). Fractional constant elasticity of variance model. Time Series and Related Topics, 149–164.
..........Conference Papers..........
 C.T. Ng and M.H. Na (2015). A note on the fast maximum likelihood estimation algorithm of factor analysis. ISSAT 2015 Proceedings, Vietnam, 62–63 M.H. Na,
 C.T. Ng, H.C. Song, and E.H. Hong (2015). Reliability analysis of tires using field data. ISSAT 2015 Proceedings, Vietnam, 74–78
 C.T. Ng (2015). High dimensional factor analysis of time series. ITISE 2015 Proceedings, Spain, 733–741 J. Ko and
 C.T. Ng (2015). Effective linking of crop modeling and remote sensing. ITISE 2015 Proceedings, Spain, 481–492
 H. Joe, J. Qu, C.T. Ng and Y. Lee. (2008). Composite likelihood approach to stochastic volatility models. IASC 2008 Proceedings, Japan, 775–783
