Research Page for Z.-Q. John Lu

CompBio

MedStat

Research interests

Bayesian statistics and applications in data assimilation and genomics.
Computational biology: microscopic imaging and multiplexed assays.
Quantitative medical imaging: variability, statistical decision, and functional data analysis.
Past work
Statistics for complex systems: time series analysis.
Presentations Given Recently.
On-line library.
My general interest is in cross-disciplinary statistical research. I have worked on important societal problems in numerical weather prediction, polymer mass spectrometry, gene expression microarray experiments, and more recently in cell metrology and cancer imaging biomarkers. My statistical expertise is in broad statistical methodology and statistical theory. In the past I have worked extensively in time series analysis and multivariate statistics. My current interests are in Bayesian methods, functional data analysis, computational biology, and statistical imaging analysis. Here is my philosophy about what I do every day and why it is fun to work on interdisciplinary research problems.
- A collection of some interesting reflections from some prominent statisticians.
- A partial list of who's who of cross-disciplinary mathematical scientists.

NEWZ.Q. J. Lu, N. Lowhorn, W. Wong-Ng, W. Zhang et al (2009). Statistical analysis of a round-robin measurement survey of two candidate materials for a Seebeck coefficient Standard Reference Material. NIST Journal of Research, Vol.114, No.1, 37-55.
Nonparametric Functional Data Analysis: Theory And Practice (Book Review), Technometrics, Volume 49, Number 2, May 2007, 226.
N. Machkour-Deshayes, J. Stoup, Z. Q. Lu, J. Soons, U. Griesmann, R. Polvani (2006) Form-profiling of Optics Using the Geometry Measuring Machine and the M-48 CMM at NIST. Journal of Research of NIST, September-October 2006, Vol.111, No.5, pp.373-384.
Book contribution to Modeling and Forecasting Financial Data (Kluwer, 2002): Chapter 5. Local Polynomial Prediction and Volatility Estimation in Financial Time Series.
Experimental design for spatial and adaptive observations. Z.Q.Lu, L.M.Berliner, C.Snyder. In Studies in Atmospheric Sciences, Lecture Notes in Statistics, Vol.144, Springer-verlag, 2000.
Some statistical considerations associated with the data assimilation of precipitation observations. R.M. Errico, L.Fillion, D.Nychka, Z.Q. Lu, Quarterly Journal of the Royal Meteorological Society. Vol. 126, no. 562, part A 339-360. January 01, 2000.

Statistical Design for Adaptive Weather Observations (L. M. Berliner, Z. Q. Lu, C. Snyder). Journal of the Atmospheric Sciences: Vol. 56, No. 15, 2536-2552. August, 1999.

Markov switching time series models with application to a daily runoff series (Z.Q. Lu, L. M. Berliner). Water Resources Research, Vol. 35, No. 2, 523-534. Feb. 1999.
Nonparametric Regression with Singular Design. Revised version of the paper:"Nonparametric function estimation for fractal and chaotic data". Journal of Multivariate Analysis, 1999, Vol.70, 177-201. Here it is the ps file, pdf file.
In this paper, I develop what it is the precise meaning of "intrinsic dimensionality" associated with analyzing multivariate data, dispelling the scare that is usuallly thrown into high-dimensional modeling in the term "curse of dimensionality". Note that the same theory applies to nonparametric functional data analysis, i.e. regression models in which the covariates take on discretely-sampled measurements of curves in some functional space.

Multivariate local polynomial fitting for martingale nonlinear regression models. Annals of Instititute of Statistical Mathematics , Vol.51, No.4, 691-706. December, 1999.
Estimating Local Lyapunov Exponents (Z.Q. Lu, R.L. Smith). Invited paper in Nonlinear Dynamics and Time Series , editors Colleen D. Cutler and Daniel T. Kaplan. 135-151. Fields Institute Communications, Volume 11. Published by American Mathematical Society, 1997. ISBN 0-8218-0521-5.
Statistical Estimation of Local Lyapunov Exponents: Toward Characterizing Predictability in Nonlinear Systems. ps file, pdf file First version 1994, Last revision 1997, unpublished manuscript.
Multivariate locally weighted polynomial fitting and partial derivative estimation. Journal of Multivariate Analysis, 1996, 59, 187-205.

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