Research areas and selected publications

• Theory of Scientific Inference
  • Zhang, J. and Liu, C (2010). Dempster-Shafer inference with weak beliefs. To appear in Statistica Sinica.
  • Martin, R., Zhang, J., and Liu, C. (2010). Dempster-Shafer theory and statistical inference with weak beliefs. Statistical Science, 25, 72-87.
  • Ermini Leaf, D., Hui, J., and Liu, C. (2009). Statistical inference with a single observation of N(&theta, 1). Pak. J. Statist. 25.
  • Martin, R., Hwang, J., and Liu, C. (2010). General theory of inferential models I. conditional inference.
  • Martin, R., Hwang, J., and Liu, C. (2010). General theory of inferential models II. marginal inference.

• Statistical Methods
  • Edlefsen, P. T., Liu, C., and Dempster, A. P. (2009). Estimating limits from Poisson counting data using Dempster-Shafer analysis. Annals of Applied Statistics 3, 764-790.
  • Liang, F., Liu, C., and Wang, N. (2007). A robust sequential Bayesian method for identification of differentially expressed genes, Statistica Sinica, 17, 571-597.
  • Pinheiro, J. C., Liu, C. and Wu, Y. (2001). Efficient algorithms for robust estimation in linear mixed-effects models using the multivariate t-distribution, J. Comput. and Graph. Statist. 10, 249-276.
  • Liu, C. (1996). Bayesian robust multivariate linear regression with incomplete data, JASA 91, 1219-1227.

• Computational Statistics (EM and quasi-Newton algorthms, Markov Chain Monte Carlo Methods)
  • Lewandowski, A., Liu, C., and Scott Vander Wiel (2010). Parameter expansion and efficient inference. Statistical Science, 25, 533-544.
  • Liang, F., Liu, C. and Carroll, R.J. (2007). Stochastic approximation in Monte Carlo computation. JASA, 102, 305-320
  • Liu, C. and Vander Wiel, S. (2007). Statistical Quasi-Newton: A new look at least change, SIAM Journal on Optimization, 18, 1266-1285.
  • Liu, C. (2003). Alternating subspace-spanning resampling to accelerate Markov chain Monte Carlo simulation, JASA, 98, 110-117
  • Liu, C., Rubin, D. B., and Wu, Y. (1998). Parameter expansion to accelerate EM: the PX-EM algorithm, Biometrika 85, 755-770
  • Liu, C. (1998). Information matrix computation from conditional information. Biometrika 85, 973-979
  • Liu, C. and Rubin, D. B. (1994). The ECME algorithm: a simple extension of EM and ECM with faster monotone convergence. Biometrika 81, 633-648.

• Applied Statistics

• Buvaneswari, A., Graybeal, J. M., James, D. A., Lambert, D., Liu C., and MacDonald, M., W. (2007). A statistical view of the transient signals that support a wireless call. Technometrics, 49, 305-317.
• Liu, C. and Sun, D. X. (2000). Analysis of interval-censored data from fractionated experiments using covariance adjustment, Technometrics 42, 353-365.
• Lambert, D. and Liu, C. (2006). Adaptive thresholds: monitoring streams of network counts, JASA 101, 78-88.
• Hopke, P. K., Liu, C. and Rubin, D. B. (2001). Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic, Biometrics 57, 22-33.
• Clark, L., Cleveland, W. S., Denby, L., and Liu, C. (1999). Modeling customer survey data (with Discussion), in Case Studies in Bayesian Statistics, IV, 3-57, Eds. B. P. Carlin, A. L. Carriquiry, C. Gatsonis, A. Gelman, R. E. Kass, I. Verdinelli, and M. West.
• Gelman, A., King, G., and Liu, C. (1998). Not asked or not answered: multiple imputation for multiple surveys (with discussion), JASA 93, 846-874.
• Liu, C. and Stock, J. M. (1993). Quantitative determination of uncertainties in seismic refraction prospecting, Geophysics 58, 553-563.