Nonparametric and semiparametric statistics with focus on
high-dimensional data analysis, quantile regression, data-driven decision
making, survival analysis.
Associate Editor of Journal of the Royal Statistical Society, Series B (04/2013-08/2016)
Associate Editor of Biometrics
Associate Editor of Journal of the American Statistical Association
Associate Editor of Annals
of Statistics (01/2016-present)
Co-editor, special issue of Econometrics
and Statistics on Quantile Regression and Semiparametric Methods,
Selected Papers (*
(Acknowledgement: The research of Dr. Wang has been
supported by NSF since 2007.)
Link to supplement
R package: quantoptr
Xu, G.J., Sit, T., Wang, L. and Huang, C-Y. (2017)
regression under general biased sampling scheme. Journal of the American
Statistical Association, 112, 1571-1586.
- Liqun Yu, Nan Lin and Lan
Wang (2017) A
parallel algorithm for large-scale nonconvex
penalized quantile regression. Journal
of Computational and Graphical Statistics, 935-939.
- Peng, B.*, Wang,
L. and Wu, Y. (2016) An Error Bound
for L_1-norm Support Vector Machine
Coefficients in Ultra-high Dimension. Journal of Machine Learning Research, 17(236):1-26.
- Jinyuan Chang,Wen Zhou, Wen-Xin Zhou and Lan Wang. (2017) Comparing Large
Covariance Matrices under Weak Conditions on the Dependence Structure and
its Application to Gene Clustering. Biometrics, 73, 31-41.
Link to online
- Lan Wang.
(2016+) Nonconvex Penalized Quantile Regression: a Review of Methods,
Theory and Algorithms for High-dimensional Heterogeneous Data Analysis.
Invited book chapter for Handbook
of Quantile Regression, edited by Roger Koenker,
Victor Chernozhukov, Xuming
He and Limin Peng.
- Hong, H. G., Wang,
L. and He, X. (2016) A
data-driven approach to conditional screening of high dimensional
variables. Stat, 5,
- Wang, L.
and Sherwood, B*. (2016) Invited
discussion on “Posterior inference in Bayesian quantile regression with
asymmetric Laplace likelihood” by Yang, Wang and He, International Statistical Review,
B*. and Wang, L. (2016) Partially linear
additive quantile regression in ultra-high dimension. Annals
of Statistics, 44, 288-317.
Link to online
Zhang, X., Wu, Y., Wang, L. and Li. R. (2016) A consistent information
criterion for support vector machine in diverging model space. Journal
of Machine Learning Research, 17(16),
- Wang, L., Peng, B*. and Li., R.
high-dimensional nonparametric multivariate test for mean vector. Journal of the American Statistical
Association, 110, 1658-1669.
X., Wu, Y., Wang, L. and Li.,
R. (2016) Variable
selection for support vector machines in moderately high dimensions.
of the Royal Statistical Society, Series B, 78, 53-76.
B*. and Wang, L. (2015) An iterative
coordinate-descent algorithm for high-dimensional nonconvex penalized
quantile regression. Journal of Computational and Graphical
Statistics, 24(3), 676-694.
- Wang, L., Sherwood, B*. and Li,
R. (2014) Discussion
on “Estimation and Accuracy after Model Selection" by Brad Efron. Journal
of the American Statistical Association, 109, 1007-1010.
L., Liang, H. and Wang, L. (2014) Generalized
additive partial linear models for clustered data with diverging number of
covariates using GEE. Statistica Sinica,
A., Wang, L. and Rudser, K.
quantile regression with recursive partitioning based weights. Biostatistics, 15, 170-181.
- Huixia Wang and Lan
Wang. (2014) Quantile regression
analysis of length-biased survival data. Stat, 3, 31-47.
- Wang, L, Yongdai
Kim and Runze, Li .
non-convex penalized regression in ultra-high dimension. Annals of Statistics, 41,
- Wang, L., Kai, B., Cedric,H. and Tsai, CL. (2013) Penalized
profiled semiparametric estimating functions. Electronic Journal of Statistics,
B*., Wang, L. and Zhou, A.
(2013) Weighted quantile
regression for analyzing health care cost data with missing covariates.
in Medicine, 32, 4967-4979.
X., Wang, L. and Hong, H.
model-free nonlinear feature screening for high-dimensional heterogeneous
data. Annals of Statistics, 41, 342-369. Link to an
of the typo in Example 3 of the paper.
X.H., Huang, C.Y. and Wang, L. (2013) Quantile regression for recurrent gap time
data. Biometrics, 69, 375-385.
- Quantile regression
of analyzing heterogeneity in ultra-high dimension (2012), by Lan
Wang, Yichao Wu and Runze
Journal of the American Statistical
Here is an online
supplemental file that contains additional technical details.
regression under possible model misspecification (2011), by Lan Wang,
Nonparametric Statistics and Mixture
Models: A Festschrift in Honor of Thomas P. Hettmansperger
(ed by Hunter, Richards and Rosenberger), 317-335.
- Semiparametric modeling
and estimation of heteroscedasticity in regression analysis of
cross-sectional data (2010), by Ingrid Van Keilegom
and Lan Wang, Electronic
Journal of Statistics, 4, 133-160.
- Local rank
inference for varying coefficient models (2009), by Lan Wang,
Bo Kai and Runze Li, Journal of the
American Statistical Association, 104, 1631-1645.
weighted censored quantile regression (2009), by Huixia
Wang and Lan Wang, Journal of the American Statistical
Association, 104, 1117-1128. Here is a remark of
Wilcoxon-type smoothly clipped absolute deviation method (2009), by
Lan Wang and Runze Li, Biometrics,
65(2), 564-571. [Web
generalized Bayesian information criterion (2009), by Lan Wang,
Biometrika, 96(1), 163-173.
model selection and data-driven smooth tests for longitudinal data in the
estimating equations approach (2009), by Lan Wang and Annie Qu,
Journal of the Royal Statistical
Society, Series B, 71(1),
test for checking lack-of-fit of quantile regression model under random
censoring (2008), by Lan Wang, Canadian Journal of Statistics,
- An ANOVA-type
nonparametric diagnostic test
for heteroscedastic regression models (2008), by Wang, L., Akritas, M. G., and Van Keilegom,
I., Journal of Nonparametric Statistics, 20(5):365–382.
- Assessing the
adequacy of variance function in heteroscedastic regression models
(2007), by Lan Wang and Xiao-Hua Zhou, Biometrics, 63(4), 1218-1225.
tests in regression models with omnibus alternatives and bounded
influence (2007), by Lan Wang and Annie Qu, Journal of
the American Statistical Association, 102, 347-358.
- A simple
nonparametric test for diagnosing nonlinearity in Tobit median regression
model (2007), by Lan Wang, Statistics and Probability
Letters, 77(10), 1034-1042.
test for the form of parametric regression with time series errors
(2007), by Lan Wang and Ingrid Van Keilegom,
Statistica Sinica, 17, 369-386.
for covariate effects in fully nonparametric ANCOVA model (2006), by Lan
Wang and Michael. G. Akritas, Journal of the American
Statistical Association, 101, 722-736.
heteroscedastic ANOVA with large number of levels (2006), by Lan
Wang and Michael. G. Akritas, Statistica Sinica,
- A fully
nonparametric diagnostic test for homogeneity of variances (2005), by Lan
Wang and Xiao-Hua Zhou, Canadian Journal of Statistics,
Vol. 33, No 4, pp. 545-558.