Research
Software for Big Data Computing and Analysis
Current Efforts: supr3 --- an experimental R package for distributed and parallel statistical
computing
Early Efforts
Selected Papers
Foundations of Statistical Modeling: Auto-modeling
Foundations of Statistical Inference: Inferential Models
Liu, C. (2023). Another look at the problem of many-normal-means , arXiv:2207.05190
Liu, C. and Martin, R. (2023). Elucidating Inferential Models with the Cauchy Distribution , arXiv:2301.05257
Zhang, R., Zhu, Y., and Liu, C. (2023). On Existence Theorems for Conditional Inferential Models , arXiv:2301.05135
Yang, J., Wang, X., and Liu, C. (2023). Partial Conditioning for Inference of Many-Normal-Means with Hölder Constraints , to appear in International Journal of Approximate Reasoning 159 ; see also arXiv:2301.04512
Liu, C. and Martin, R. (2021).
Comment: Settle the unsettling: an inferential models perspective , Statistical Science 36(2), 196-200.
Liu, C. and Martin, R. (2020). Inferential models and possibility measures , in Handbook of Bayesian, Fiducial, and Frequentist Inference. arXiv:2008.06874
Qiu, Y., Zhang, L., and Liu, C. (2018).
Exact and efficient inference for partial Bayes problems , Electronic Journal of Statistics , 12(2), 4640-4668.
Martin, R. and Liu, C. (2015).
Marginal inferential models: prior-free probabilistic inference on interest parameters , Journal of the American Statistical Association , 110 , 1621-1631.
Martin, R. and Liu, C. (2015).
Conditional inferential models: combining information for prior-free probabilistic inference , Journal of the Royal Statistical Society, Series B , 195-217.
Martin, R. and Liu, C. (2014).
A note on p-values interpreted as plausibilities , Statistica Sinica , 24 , 1703-1716.
Martin, R. and Liu, C. (2014).
Comment: foundations of statistical inference, revisited , Statistical Science , 247-251.
Liu, C. and Martin, R. (2014).
Frameworks for prior-free posterior probabilistic inference , WIREs Computational Statistics , 7 , 77-85.
Martin, R. and Liu, C. (2013). Inferential models: a framework for prior-free
posterior probabilistic inference , Journal of the American Statistical Association , 108 , 301-313.
Ermini Leaf, D. and Liu, C. (2012). Inference about constrained parameters using the elastic belief method , International Journal of Approximate Reasoning , 53 , 709 - 727.
Computational Strategies
EM-type algorithms
Srivastava, S., DePalma, G. and Liu, C. (2019)
An Asynchronous Distributed Expectation Maximization Algorithm For Massive Data: The DEM Algorithm ,
Journal of Computational and Graphical Statistics , 28(2), 233-243.
He, Y. and Liu, C. (2012). The dynamic `expectation-conditional maximization either' algorithm , Journal of the Royal Statistical Society, Series B , 313-336.
Lewandowski, A., Liu, C., and Scott Vander Wiel (2010). Parameter expansion and efficient inference .
Statistical Science , 25, 533-544.
Liu, C., Rubin, D. B., and Wu, Y. N. (1998). Parameter expansion to accelerate EM: the PX-EM algorithm. Biometrika , 85(4), 755-770.
Liu, C. and Rubin, D. B. (1994).
The ECME algorithm: a simple extension of EM and ECM with faster monotone convergence . Biometrika , 81(4), 633-648.
Markov chain Monte Carlo (MCMC)
Lewandowski, A. and Liu, C. (2010). The sample Metropolis-Hastings algorithm.
Liang, F., Liu, C., and Carroll, R. J. (2007). Stochastic approximation in Monte Carlo computation.
Journal of the American Statistical Association , 102(477), 305-320.
Liu, C. (2003). Alternating subspace-spanning resampling to accelerate Markov chain Monte Carlo simulation. Journal of the American Statistical Association , 98(461), 110-117.
Liu, C. and Rubin, D. B. (1996).
Markov-normal analysis of iterative simulations before their convergence ,
J. Econometrics , 75 , 69-78.
Miscellaneous algorithms
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. (1998). Information matrix computation from conditional information via normal approximation. Biometrika , 85(4), 973-979.
Statistical Methods
Zhang, J., Li, J., and Liu, C. (2014).
Robust factor analysis using the multivariate t-distribution . Statistica Sinica , 291-312.
Liu, C. (2004). Robit regression: a simple robust alternative to logistic regression and probit regression , in Missing Data and Bayesian Methods in Practice , eds. A. Gelman and X. Meng.
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. and Rubin, D.B. (1998). Ellipsoidally Symmetric Extensions of the General
Location Model for Mixed Categorical and Continuous Data. Biometrika 85 , 673-688.
Liu, C. (1996).
Bayesian robust multivariate linear regression with incomplete data ,
Journal of the American Statistical Association 91 , 1219-1227.
Liu, C. (1995).
Missing data imputation using the multivariate t distribution . Journal of multivariate analysis , 53 (1), 139-158.
Liu, C. (1993).
Bartlett decomposition of the posterior distribution of
the covariance for normal monotone ignorable missing data> ,
Journal of Multivariate Analysis 46 , 198-206.
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.
Lambert, D. and Liu, C. (2006). Adaptive thresholds:
monitoring streams of network counts,
Journal of the American Statistical Association 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.
Liu, C. and Sun, D. X. (2000).
Analysis of interval-censored data from fractionated experiments using
covariance adjustment,
Technometrics 42 , 353-365.
Gelman, A., King, G., and Liu, C. (1998).
Not asked or not answered: multiple imputation for multiple surveys
(with discussion) ,
Journal of the American Statistical Association 93 , 846-874.
Liu, C. and Stock, J. M. (1993).
Quantitative determination of uncertainties in seismic refraction
prospecting , Geophysics 58 , 553-563.
Gatsonis, C. A., Normand, S. L., Morris, C., and Liu, C. (1992).
Geographic variation of procedure utilization: a hierarchical model approach ,
Medical Care , 31 , YS54-59.
Chen, P., Xu, L., He, Z., and Liu, C. (1988).
A depth series model-based interpretation system for point-wise permeability, Well Logging Technology ,
12 (4), 10-17.
Copyright © 2015 Chuanhai Liu. All rights reverved.
