Faming Liang
Professor, Department of
Statistics,
Texas A&M University, College Station, TX 77843-3143.
Office: BLOC
406D; Phone:
(979) 8458885; Email:
fliang@stat.tamu.edu
Courses taught:
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Computing for Statistics
-
Computer Intensive
Statistical Methods
-
Linear Model
-
Regression Analysis
-
Probability
-
Mathematical Statistics
-
Introduction to Linear
Models
-
Probability (graduate
course)
-
Statistical Inference
(graduate course)
-
Computing for Bioinformatics
(graduate
course)
Lecturing Assignment for
Semester
I, 2009-2010:
STAT414 Mathematical
Statistics
Lecture
Notes
Assignments:
Research Interests:
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Markov Chain Monte Carlo
-
Bioinformatics
-
Neural Network
-
Stochastic Optimization
-
Computational Physics
Research Group
Recent Talks
Editorial Service
-
Associate
editor, Journal of Computational and
Graphical Statistics, 2006-Present.
- Editorial Board Member, International Journal of Operations
Research and Information Systems (IJORIS)}, 2008---present.
- Editorial Board Member, Journal of Advanced Research in Statistics
and Probability, 2009--present
-
Associate editor, Biometrics,
2006-2008.
Honors
-
Elected member,
International Statistical Institute (ISI), 2005.
-
Statistica Sinica, invited paper, 2001 Joint
Statistical Meeting.
Selected Publications:
-
Kendall, W.S., Liang, F., and
Wang, J.S. (2005) (Editors) Markov Chain Monte
Carlo: Innovations
and Applications. World Scientific: Singapore. ISBN
981-256-427-6.

- Liang, F., Wu, M., and Tian,
Y.
(2008) Bayesian
LatentChIP.
- Wu, M. and Liang, F.
(2009) Testing multiple hypotheses using population information
of samples. Code , Supplementary Material.
-
Wong, W.H. and Liang, F.
(1997) Dynamic weighting in Monte
Carlo and optimization, Proc.
Natl.
Acad. Sci. USA, 94, 14220-14224.
-
Liang, F. and Wong, W.H.
(1999) Dynamic weighting in
simulations of spin systems, Phys.
Lett. A, 252, 257-262.
-
Cong, J., Kong, T., Xu, D.,
Liang, F., Liu, J.S., and Wong, W.H. (1999) Relaxed simulated tempering
for VLSI floorplan designs, Proc. Asia and South Pacific
Design Automation Conf., Hong Kong, pp13-16.
-
Cong, J., Kong, T., Xu, D.,
Liang, F., Liu, J.S., and Wong, W.H. (2000) Dynamic weighting Monte
Carlo for constrained floorplan design in mixed signal
application,Proc. Asia and South Pacific Design Automation
Conf., Japan.
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Sanderson P, Taylor D., Ali
M., Liew S.C., Couturier S., Lee G., Truong Y., Liang F., Gin K. and
Holden H. (1999) Development of a methodology for monitoring
variations in turbid waters draining modified wetlands in southeast
Sumatra, Indonesia: preliminary results for suspended sediments,
Eighth International Symposium on the Interactions Between Sediments
and Water}, Beijing, pp. 13-17.
-
Liu, J.S., Liang, F., and
Wong. W.H. (2000) The use of
multiple-try method and local optimization
in Metropolis sampling, J. Amer. Statist. Assoc.,95,
121-134.
-
Liang, F. and Wong. W.H.
(2000) Evolutionary Monte Carlo
sampling: applications to $C_p$
model sampling and change-point problem. Statistica Sinica,10,
317-342.
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Truong, Y. K., Liang, F.,
Sanderson, P. G., Taylor, D. and Liew, S. C. (2000) M onitoring
variations in turbid waters draining modified wetlands in
southeast Su matra, Indonesia: A functional data analytic approach.
In Nonparametric approach to Knowledge Discovery, Nara,
Japan, December 14-17, 2000. Proceedings.
-
Liu, J.S., Liang, F., and
Wong. W.H. (2001) A theory for dynamic
weighting in Monte Carlo, J.
Amer. Statist. Assoc., 96, 561-573.
-
Liang, F. and Wong. W.H.
(2001) Real-parameter evolutionary
sampling with applications in
Bayesian Mixture Models, J. Amer. Statist. Assoc., 96,
653-666.
-
Liang, F., Truong, Y.K. and
Wong, W.H. (2001) Automatic
Bayesian model averaging for
linear regression and applications in Bayesian curve fitting.
Statistica Sinica , 11, 1005-1029.
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Liang, F. and Wong, W.H.
(2001) Evolutionary Monte Carlo for
Protein Folding
simulations, Journal of Chemical Physics , 115,
3374-3380.
-
Liang, F. (2002) Some
connections between Bayesian and non-Bayesian methods for regression
model selection. Statistics & Probability
Letters
, 57,
53-63.
-
Liang, F. (2002) Dynamically
Weighted Importance Sampling in Monte Carlo Computation, J.
Amer. Statist. Assoc. , 97, 807-821.
-
Liang, F. (2003) An
Effective
Bayesian Neural Network Classifier with a Comparison Study to Support
Vector Machine, Neural Computation, 15,
1959-1989.
-
Liang, F. (2003) Use
of
sequential structure in simulation from high dimensional systems, Physical Review E, 67, 56101-56107.
-
Zhang, J., Liang, F., Dassen, W.
and de Gunst, M. (2003) Search
for Haplotype-Interactions that
are
susceptible to type I diabetes using unphased genotype data, American J. Human Genetics, 73, 1385-1401.
-
Liang, F. (2004). Generalized
1/k-Ensemble Algorithm, Physical
Review E, 69,
66701-66707.
-
Liang, F. (2004) Annealing
Contour Monte Carlo for Structure Optimization in an Off-lattice
Protein Model. Journal of
Chemical Physics, 120,
6756-6763. (This paper is
selected by editors expert for re-publication in the April 1,
2004 issue of Virtual Journal
of Biological Physcis Research.)
-
Liang, F. (2004) Annealing
contour Monte Carlo for neural network training. Proceedings on
Cybernetics and Informatics Technologies, Systems and Applications,
Volume III, pp.130-135.
-
Liang, F. and Kuk, Y.C.A. (2004) A finite population
estimation study with Bayesian neural
networks. Survey
Methodology, 30,
219-234.
-
Liang, F. (2005) Bayesian
neural networks for non-linear time series forecasting.
Statistics
and Computing, 15, 13-29.
-
Liang, F. and Liu, C.
(2005) Efficient MCMC
estimation of discrete distributions. Computational Statistics
and Data Analysis, 49,
1039-1052.
-
Liang, F. (2005) Evidence
Evaluation for Bayesian Neural Networks. Neural Computation, 17, 1385-1410.
-
Liang, F. (2005) Generalized
Wang-Landau algorithm for Monte Carlo Computation. J. Amer. Statist. Assoc., 100, 1311-1327.
-
Liang, F. (2005) Determination
of normalizing constants for simulated tempering. Physica A, 356, 468-480.
-
Liang, F. (2005). Annotated
bibliography: Advanced Markov chain Monte Carlo methods. ISBA Bulletin, 12(4), 2-5.
-
Liang, F. and Huang, J. (2006)
Book Review: Statistical and Computational Inverse
Problems. Technometrics,
48, 146.
-
Liang, F. (2006) A theory on
flat histogram Monte Carlo algorothms. Journal of Statistical Physics, 122, 511-529.
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Zhu, H., Liang, F., Gu, M. and Peterson, B. (2006)
Stochastic Approximation algorithms for estimation of spatial mixed
models. In Handbook of
Computing and Statistics with Applications, Vol. 1 (eds. S.Y. Lee), Elsevier.
pp.399-421.
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Liang, F., Liu, C. and Wang, N.
(2007) A sequentail Bayesian procedure
for
identification of
differentially expressed genes. Statistica
Sinica, 12, 571-597.
-
Liang, F., Liu, C. and Carroll, R.J. (2007) Stochastic
Approximation in Monte Carlo Computation. J. Amer. Statist. Assoc., 102, 305-320.
-
Liang, F. and Wang, N. (2007) Dynamic
Hierarchical Clustering of Gene
Expression Profiles. Pattern
Recognition Letters, 28, 1062-1076.
-
Liang,
F. (2007) Use of SVD-based probit
transformation in clustering gene
expression
profiles. Computational
Statistics and Data Analysis, 51, 6355-6366.
-
Liang, F. (2007) Continuous
Contour
Monte Carlo for Marginal Density
Estimation with an Application
to a Spatial Statistical Model, Journal
of Computational and Graphical
Statistics, 16(3),
608-632.
-
Liang, F. (2007) Annealing
Stochastic
Approximation Monte Carlo for Neural Network Training. Machine Learning, 68(3), 201-233.
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Cheon, S. and Liang, F.
(2008) Phylogenetic Tree
Reconstruction Using
Sequential Stochastic
Approximation Monte Carlo. BioSystems, 91, 94-107.
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Liang, F. (2008) Stochastic
Approximation Monte Carlo for
MLP Learning. In Encyclopedia
of Artificial Intelligence, (eds. J.R.R. Dopico, J.D. de
la Calle, and A.P. Sierra), pp.1482-1489.
-
Zhang, J., J Rggieli, M. Schipper, M. Entius, F. Liang, J.
Koerselman, H Ruven, Y van der Graaf, D. Grobbee, and P. Doevendans
(2008) Inflammatory gene
haplotype-interaction networks involved
in coronary collateral formation.
Human
Heredity, 66, 252-264.
-
Liang, F. and Zhang, J. (2008) Estimating FDR under
general dependence using stochastic approximation. Biometrika, 95(4), 961-977.
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Liang, F. (2008) Clustering
gene expression profiles
using mixture model ensemble averaging approach. JP Journal of Biostatistics, 2(1), 57-80.
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Zhang, J. and Liang, F. (2008) Convergence of stochastic
approximation under irregular conditions. StatisticaNeerlandica, 62, 393-403.
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Yuan, R., Ding, Y., and Liang, F. (2008) Adaptive
Evolutionary Monte Carlo for Optimizations with Applications to Sensor
Placement Problems. Statistics
and Computing, 18,
375-390.
-
Liang, F. (2009) Improving SAMC Using
Smoothing Methods: Theory and
Applications to Bayesian Model Selection Problems. The Annals of Statistics, 37, 2626-2654.
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Liang, F. (2009) On
the use of SAMC for Monte Carlo
integration. Statistics &
Probability Letters, 79,
581-587.
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Liang, F. and Zhang, J. (2009) Learning Bayesian Networks for
Discrete Data. Computational
Statistics
& Data Analysis, 53,
865-876.
-
Zhang, X.S., Liang, F., Srinivasan, R., and Van Liew, M.
(2009) Estimating uncertainty of
streamflow simulation using Bayesian
neural networks. Water
Resources Research, 45, W02403.
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Zhang, P., Hill, C., Xia, Y., and Liang, F. (2009)
Modeling the relationship between EDI implementation
and firm performance improvement with neural networks. IEEE Transactions on Automation Science
and Engineering, in press.
-
Liang, F. (2009) A double
Metropolis-Hastings sampler for spatial models with intractable
normalizing constants.
Journal of Statistical Computing and
Simulation, in press.
-
Cheon, S. and Liang, F. (2009) Bayesian phylogeny
analysis via stochastic approximation Monte Carlo. Molecular Phylogenetic & Evolution, 53, 394-403.
-
Wu, M., Liang, F. and Tian, Y.
(2009) Bayesian Modeling of ChIP-chip Data Using Latent Variables. BMCBioinformatics,
in press.
-
Mo, Q. and Liang, F. (2009) Bayesian modeling of
ChIP-chip data through a high-order Ising model. Biometrics, in press.
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