Research

Interests

• Analysis of time series of everything
• Monte Carlo Methods, Statistical Computing and Bayesian Analysis
• Statistical Applicatons in Science, Engineering and Business.

Book

• Nonlinear Time Series Analysis (with Ruey Tsay) and its accompanying site for additional material

 

Papers

• [1] Chen, R. and Tsay, R.S. (1991) `On the ergodicity of TAR(1) processes’, The Annals of Applied Probability, 1, 613-634.
• [2] Chen, R. and Tsay, R.S. (1993) `Functional coe±cient autoregressive models’, Journal of American Statistical Association, 88, 298-308.
• [3] Chen, R. and Tsay, R.S. (1993) `Nonlinear additive ARX models’, Journal of American Statistical Association, 88, 955-967.
• [4] Liu, J.S. and Chen, R. (1995) `Blind deconvolution via sequential imputation’, Journal of American Statistical Association, 90, 567-576.
• [5] Chen, R., Liu, J.S. and Tsay, R.S. (1995) `Additivity tests for nonlinear autoregressive models’, Biometrika, 82, 369-383.
• [6] Chen, R. (1995) `Threshold variable selection of open-loop threshold AR models’, Journal of Time Series Analysis, 16, 461-481
• [7] Chen, R. and Li, T. (1995) `Blind restoration of linearly degraded discrete signals by Gibbs sampler’, IEEE Transactions on Signal Processing, 43, 2410-2413
• [8] Chen, R. (1996) `A nonparametric multi-step prediction estimator in Markovian structures’, Statistica Sinica, 6, 603-615
• [9] Chen, R. and Liu, J.S. (1996) `Predictive updating methods with applications to Bayesian classiffication’, Journal of the Royal Statistical Society, Series B, 58, 397-415
• [10] Chen, R. and Tsay, R.S. (1996) `Nonlinear transfer functions’, Journal of Nonparametric Statistics, 6, 193-204.
• [11] Cheng, Q., Chen, R. and Li, T. (1996) `Simultaneous wavelet estimation and deconvolution of reflection Seismic signals via Gibbs sampler’, IEEE Transactions on Geoscience and Remote Sensing, 34, 377-384
• [12] Chen, R. (1996) `Incorporating extra information in nonparametric smoothing’, Journal of Multivariate Analysis, 58, 133-150
• [13] Carroll, R.J., Chen, R., Li, T-H, Newton, H.J., Schmiediche, H. and Wang, N. (1997) `Trends in ozone exposure in Harris County, Texas’, Journal of American Statistical Association, (discussion paper), 92, 392-415
• [14] HÄardle, W., Chen, R. and Luetkepohl, H. (1997). `A review of nonparametric time series analysis’, International Statistical Review, 65, 49-72
• [15] Linton, O. Chen, R. Wang, N. and HÄardle, W. (1997). `An analysis of transformation for additive nonparametric regression’, Journal of American Statistical Association, 92, 1512-1521
• [16] Liu, J.S. and Chen, R. (1998) `Sequential Monte Carlo methods for dynamic systems’, Journal of American Statistical Association, 93, 1032-1043
• [17] Liu, J.S. Chen, R. and Wong, W.H. (1998) `Rejection control and importance sampling’, Journal of American Statistical Association, 93, 1022-1031
• [18] Chen, R. and Fomby, T. (1999) `Forecasting with stable seasonal pattern models with an application of Hawaiian tourist data’, Journal of Business & Economic Statistics, 17, 497-504
• [19] Speed, F.M., Smith, W.B., Chen, R., and Speed, F.M. Jr (1999), `Analysis of tidal data and datums: Accessible examples of harmonic modeling with autocorrelation and imputation’, Communications in Statistics, Part A – Theory and Methods, 28, 2947-2965
• [20] Chen, R. and Liu, J.S. (2000) `Mixture Kalman Filters’, Journal of the Royal Statistical Society, Series B, 62, 493-508
• [21] Chen, R., Wang, X. and Liu, J.S. (2000) ‘Adaptive Joint Detection and Decoding in Flat-Fading Channels via Mixture Kalman Filtering’. IEEE trans. information theory, 46, 2079-2094
• [22] Wang, X. and R. Chen. (2000) ‘Adaptive MAP multiuser detection for synchronous CDMA with Gaussian and non-Gaussian noise’, IEEE trans. signal processing, 48, 2013-2028
• [23] Chen, R. and Liu, L. (2001) ‘Functional coefficient autoregressive models: estimation and tests of hypotheses’, J. Time Series Analysis, 22, 151-174
• [24] Wang, X. and R. Chen. (2001) ‘Blind Turbo equalization in Gaussian and impulsive noises’. IEEE trans. Vehicular Technology, 50, 1092-1105
• [25] Liu, L-M, Bhattacharyya, S., Sclove, S.L., Chen, R. and Lattyak, W.J. (2001) ‘Data mining on time series: an illustration using fast-food restaurant franchise data’, Computational Statistics and Data Analysis, 37, 455-476
• [26] Wang, X., Chen, R. and Liu, J.S. (2002) ‘Monte Carlo Bayesian signal processing for wireless communication’, IEEE trans. VLSI Signal Process, 30, 89-105
• [27] Chen, R., Liu, J.S., and Wang, X. (2002) ‘Convergence Properties of the Gibbs Sampler in Some Digital Communications Problems’, IEEE trans. Signal Process, 50, 255-270
• [28] Wang, X., Chen, R. and Guo, D. (2002) ‘Delayed Pilot Sampling for Mixture Kalman Filter with Application in Fading Channels’, IEEE trans. Signal Process, 50, 241-254
• [29] Chen, R. and J.S. Liu. (2002) Discussion of ‘ Spatial-Temporal Nonlinear Filtering Based on Hierarchical Statistical Models’ by M. E. Irwin, N. Cressie, and G. Johannesson. Test, 11, 282-284.
• [30] Liang, J, Zhang, J. and Chen, R. (2002) ‘Statistical geometry of packing defects of lattice chain polymer for enumeration and sequential Monte Carlo method’, Journal of Chemical Physics, 117, 3511-3521
• [31] Guo, D. Wang, X. and Chen, R. (2003) ‘Nonparametric Adaptive Detection in Fading Channels Based on Sequential Monte Carlo and Bayesian Model Averaging’, Annuals of Institute of Statistical Mathematics, 55, 423-436.
• [32] Zhang, J., R. Chen, C. Tang and J. Liang (2003) ‘Origin of scaling behavior of protein packing density: A sequential Monte Carlo study of compact long chain polymer’, Journal of Chemical Physics, 118, 6102-6109
• [33] Chen, R., Yang, L. and Hafner, C. (2004) ‘Nonparametric multi-step prediction in time series’, Journal of the Royal Statistical Society, Series B. 66, 669-686.
• [34] Guo, D., Wang, X., and Chen, R.(2004) `Wavelet-based Sequential Monte Carlo Blind Receivers in Fading Channels with Unknown Channel Statistics’, IEEE Transactions on Signal Processing. 52, 227-239
• [35] Zhang, J., Chen, Y., Chen, R., and Liang, J. (2004) `Importance of chirality and reduced flexibility of protein side chains: A study with square and tetrahedral lattice models’, Journal of Chemical Physics, 121, 592-603
• [36] Hjellvik, V., Chen, R., and Tjostheim, D. (2004) ‘Nonparametric estimation and testing in panels of intercorrelated time series’, Journal of Time Series Analysis 25, 831-872
• [37] Guo, D., Wang, X. and Chen, R. (2004) ‘Multilevel Mixture Kalman Filter’, EURASIP Journal on Applied Signal Processing, Special issue on Particle Filtering, 15, 2255-2266.
• [38] Guo, D., Wang, X. and Chen, R. (2005) ‘New Sequential Monte Carlo Methods for Nonlinear Dynamic Systems’, Statistics and Computing. 15, 135-147
• [39] Lin, M., Zhang, J., Cheng, Q. and Chen, R. (2005) `Independent particle filters’, Journal of American Statistical Association, 100, 1412-1421.
• [40] Liu, J.M, Liu, L-M and Chen, R. (2006) `Modeling hourly electricity loads using a semiparametric time series approach’, Journal of Forecasting, 25, 537-559.
• [41] Zhang, J., Chen, R. and Liang, J. (2006) ‘Empirical potential function for simpliffied protein models: combining contact and local sequence structure descriptors’, PROTEINS: Structure, Function, and Bioinformatics, 63, 949-960.
• [42] Zhang, J., Lin, M., Chen, R., Liang, J. and Jun S. Liu (2007) Monte Carlo sampling of Near-Native structures of proteins with applications’, PROTEINS: Structure, Function, and Bioinformatics, 66, 61-68.
• [43] Wu, S, and Chen, R. (2007) `Threshold variable selection and threshold variable driven switching autoregressive models’, Statistica Sinica, 17, 241-264.
• [44] Zhang, J.L., Lin, M, Liu, J.S. and Chen. R. (2007) `Lookahead and piloting strategies for variable selection’, Statistica Sinica, 17, 985-1005.
• [45] Chen, C.T., Chen, R. and Bassett, G.W. (2007) ‘Fundamental Indexation via Smoothed Cap Weights’, J. Finance and Banking, 31, 3486-3502.
• [46] Lin, M., Chen, R. and Liang, J. (2008) ‘Statistical geometry of lattice chain polymers with voids of defined shapes: Sampling with strong constraints’, J. Chemical Physics, 128(084903), 1-12
• [47] Zhang, J., Lin, M., Chen, R., Wang, W. and Liang, J. (2008) ‘Discrete State Model and Accurate Estimation of Loop Entropy of RNA Secondary Structures’, J. Chemical Physics, 128(125107), 1-10
• [48] Lin, M., Lu, H., Chen, R. and Liang, J. (2008) ‘Generating properly weighted ensemble of conformations of proteins from sparse or indirect distance constraints’, J. Chemical Physics, 129(094101), 1-13.
• [49] Feng, X., Chen, R. and Bassett, G.W. (2008) ‘Quantile Momentum’, Statistics and Its Interface, 1, 243-254.
• [50] Cai, A.M., Tsay, R.S. and Chen, R. (2009) `Variable selection in linear regression with many predictors’, J. Computational and Graphical Statistics, 18, 573-591
• [51] Zhang, J., Dundas, J., Lin, M., Chen, R., Wang, W. and Liang, J. (2009) `Prediction of geometrically feasible three dimensional structures of Pseudoknotted RNA through free energy’, RNA, 15, 2248-2263.
• [52] Liu, J.M., Chen, R. and Yao, Q. (2010) `Nonparametric transfer function models’, J. Econometrics, 157 151-164.
• [53] Lin, M., Chen, R. and Mykland, P. (2010) ‘On generating Monte Carlo samples of continuous diffusion bridges’, Journal of American Statistical Association, 105, 820-838.
• [54] Chen, R., Lin, M. and Guo, R. (2010) `Self-Selection in Decision to Withdraw IPOs’, Journal of American Statistical Association, 105, 1297-1309.
• [55] Kang, Z., Zhang, L. and Chen, R. (2010) `Forecasting return volatility in the presence of microstructure noise’, Statistics and Its Interface, 3, 145-158.
• [56] Chen, R., Liang, H. and Wang, J. (2011) ‘Determination of linear components in additive models’, Journal of Nonparametric Statistics, 23, 367-383.
• [57] Lin, M., Zhang, J., Lu, H-M, Chen, R. and Liang J. (2011) ‘Constrained proper sampling of conformations of transition state ensemble during protein folding’. Journal of Chemical Physics, 134(075103) 1-13.
• [58] Chen, S., Chen, R., Ardell, G. and Lin, B. (2011) ‘End-of-day stock trading volume prediction with a two-component hierarchical model’, Journal of Trading, summer, 1-8.
• [59] Wang, J., Hua, L. and Chen, R. (2012) ‘A state-space model approach for modeling HIV infection dynamics’, Journal of Time Series Analysis, 33, 841-849.
• [60] Chen, S., Min, W. and Chen, R. (2013) ‘Model identiffication for time series with dependent innovations’, Statistica Sinica, 23, 873-899
• [61] Lin, M., Chen, R. and Liu, J.S. (2013) ‘Lookahead strategies for sequential Monte Carlo’, Statistical Science, 28, 69-94
• [62] Cheng, J., Xie, M., Chen, R. and Roberts, F. (2013) ‘A latent source model to detect multiple spatial clusters with application in a mobile sensor network for surveillance of nuclear materials’, Journal of American Statistical Association, 108, 902-913.
• [63] Li, W., Tan, Z., and Chen, R. (2013) ‘Two-stage important sampling with mixture proposals’, Journal of American Statistical Association}, 108, 1350-1360.
• [64] Liu, X., Cai, Z. and Chen, R. (2015), ‘Functional Coefficient Seasonal Time Series Model with an Application of Hawaii Tourism Data’, Computational Statistics, 33, 719-744.
• [65] Zheng, T., Xiao, H. and Chen, R. (2015) ‘Generalized ARMA Models with Martingale Difference Errors’, Journal of Econometrics, 189, 492-506
• [66] Li, W., Tan, Z., and Chen, R. (2016) ‘Efficient Sequential Monte Carlo with Multiple Proposals and Control Variates’, Journal of American Statistical Association, 111, 298-313
• [67] Liu, X. and Chen, R. (2016) ‘Regime-switching factor models for high-dimensional time series’, Statistica Sinica, 26, 1427-1451
• [68] Liu, X., Xiao, H. and Chen, R. (2016) ‘Convolutional Autoregressive Models for Functional Time Series’, Journal of Econometrics, 194, 263-282
• [69] Lin, M., Suess, E., Shumway, R. and Chen, R. (2016), ‘Bayesian deconvolution of signals observed on arrays’, J. Time Series Analysis, 37, 837-850.
• [70] Chang, K., Chen, R. and T. Fomby, T., (2017) ‘Prediction-based adaptive compositional model for seasonal time series analysis’, Journal of Forecasting, 36, 842-853
• [71] Zheng, T. and Chen, R. (2017) ‘Dirichlet ARMA models for compositional time series’, J. Multivariate Analysis, 158, 31-46.
• [72] Grelaud, A., Mitra, P., Chen, R. and Xie, M. (2018) ‘A dynamic system approach to real time nuclear source detection with mobile sensor networks’, Applied Stochastic Models in Business and Industry, 34, 4-19
• [73] Zhang, B. and Chen, R. (2018) ‘Nonlinear time series clustering based on Kolmogorov-Smirnov 2D statistic’, Journal of Classification, 35, 394-421
• [74] Zhao, Z., Zhang, Z. and Chen, R. (2018) ‘Modeling Maxima with Autoregressive Conditional Fréchet Model’. J. Econometrics, 207, 325-351.
• [75] Wang, D., Liu, X. and Chen, R. (2019) ‘Matrix factor models for high dimensional time series’, J. Econometrics, 208, 231-248
• [76] Wei, X., Zhang, P., Chen, R. and Zhou, Z. (2019) ‘A nonparametric Bayesian framework for short-term wind power probabilistic forecast’, IEEE Transactions on Power Systems, 34, 371-379
• [77] Chen, Y, Tsay, R.S. and Chen, R. (2020) ‘Constrained factor models for high-dimensional matrix-variate time series’, Journal of American Statistical Association, 115, 775-793.
• [78] Liu, X. and Chen, R. (2020) ‘Threshold factor models for high-dimensional time series’, J. Econometrics, 216, 53-70
• [79] Cai, C, Chen, R, Xie, M (2020). Individualized inference through fusion learning, WIREs Comput Stat. 12, 1-10
• [80] Liu, X, Chen, R. and Tsay, R.S. (2020) ‘NTS: An R Package for Nonlinear Time Series Analysis’, The R Journal, 2, 293-310.
• [81] Chen, R., Xiao, H, and Yang, D. (2021) ‘Autoregressive models for matrix-valued time series’, J. Econometrics, 222, 539-560.
• [82] Chen, R., Yang, D. and Zhang, C.-H. (2021) Factor model for high-dimensional tensor time series’ (with discussion), J, Journal of American Statistical Association, 117. 94-132.
• —– supplement
• —– rejoinder
• [83] Zheng, T., Xiao, H. and Chen, R. (2022) ’Generalized autoregressive moving average models with GARCH errors’, Journal of Time Series Analysis, 43, 125-146
• [84] Han, Y., Chen, R. and Zhang, C.-H. (2022) ’Rank determination in tensor factor model’, Electronic Journal of Statistics, 16, 1726-1803.
• [85] Cai, C., Chen, R. and Xiao, H. (2022) ’KoPA: Automated Kronecker product approximation’, Journal of Machine Learning Research, 23, 1-44
• [86] Xiao, H., Chen, R. and Guerard, J. (2022) ’Forecasting the U.S. unemployment rate: another look’, Wilmott, 2022(122).
• [87] Cai, C., Chen, R. and Xiao, H. (2022) ’Hybrid Kronecker product decomposition and approximation’, J. Computational and Graphical Statistics. 32, 838-852
• [88] Chen, Y. and Chen, R. (2023) ’Modeling dynamic transport network with matrix factor models: an application to international trade flow’, J. Data Science, 21, 490-507.
• [89] Cai, C., Xie, M. and Chen, R. (2023) ’Individualized group learning’, Journal of American Statistical Association, 118, 622-638
• [90] Chen, R., Ji, Y., Jiang, G., Xie, R. and Zhu, P. (2023) ’Composite index construction with expert opinion’, Journal of Business & Economic Statistics, 41, 67-79
• [91] Xiao, H., Han, Y. and Chen, R. (2023+) ’Reduced rank autoregressive models for matrix time series’, Journal of Business & Economic Statistics, in press.
• [92] Cai, C., Lin, M. and Chen, R. (2024) ’Resampling strategy in Sequential Monte Carlo for constrained sampling problems’, Statistica Sinica, 34, 1178-1214
• [93] Han, Y., Chen, R., Zhang, C.-H. and Yao, Q. (2024) ’Simultaneous decorrelation of matrix time series’, Journal of American Statistical Association, 119, 957-969.
• [94] Han, Y., Yang, D., Zhang, C.-H. and Chen, R. (2024) ’CP factor model for dynamic tensors’, Journal of the Royal Statistical Society, series B, 86, 1383 – 1413
• [95] Dong, C., Chen, R., Xiao, Z. and Liu, W. (2024) ’Functional Quantile Autoregression’, J. Econometrics, 244, 105765
  [96] Han, Y., Chen, R., Yang, D. and Zhang, C.-H. (2024) ’Tensor factor model estimation by iterative projection’, Annal of Statistics, 52, 2641-2667.
• [97] Cai, C. and Chen, R. (2025) ’State space emulation and annealed Sequential Monte Carlo for High Dimensional Optimization’, Statistica Sinica, 35, 67-89
• [98] Bolivar, S, Huang, S-C, and Chen, R (2026) ’Analysis of Tensor Time Series’, Annual Review of Statistics and Its Application, 13, 369-398.