Bing Li & John Petkau (1990). A Regression Model with Random Effects for Beer Chemistry and Canadian's Beer
Preferences. Canadian Journal of Statistics 18, No.2, 108-12.
Bing Li & Ruben Zamar (1991). Min-max Asymptotic Variance of M-Estimates of Location When Scale is Unknown.
Statistics and Probability Letters11, 139-145.
Wing Hung Wong & Bing Li (1992).
Laplaceexpansion for posterior densities of nonlinear functions of parameters.
Bing Li (1993). A deviance function for the quasi likelihood method. Biometrika 80, page 741-753.
Bing Li & Peter McCullagh (1994). Potential functions and conservative estimating functions. Annals of Statistics 22,
Susan Murphy & Bing Li (1995). Projected partial likelihood and its application to longitudinal data. Biometrika 82,
Bruce Lindsay & Bing Li (1995). Comment on the papers `The roles of conditioning in inference' by Reid, and `Inference
based on estimating functions in the presence of nuisance parameters' by Liang & Zeger. Statistical Science 10, page 175-177.
Bing Li & Ruben Zamar (1996). M-Estimates of Regression when Scale is Unknown and the Error Distribution is Possibly
Asymmetric: A Minimax Result. Canadian Journal of Statistics 24, page 193-206.
Heckman & Bing Li (1996). Nonparametric tests for bounds on the derivative of a regression function. Annals of the Nancy
Institute of Statistical Mathematics 48, page 315-336.
Bing Li & Bruce Lindsay (1996). Chi-square tests for generalized estimating equations with possibly misspecified weights.
Scandinavian Journal of Statistics 23, page 489-509.
Bing Li (1996). A minimax approach to consistency and efficiency for estimating equations.Annals of Statistics 24,
Bing Li (1997). On the consistency of generalized estimating equations. Selected proceedings of the Symposium on Estimating
Functions, page 108-129.
Bruce Lindsay & Bing Li (1997). On second-order optimality of the observed Fisher information. The Annals of
Statistics 25, 2172-2199.
Bing Li (1998). An optimal estimating equation based on the first three cumulants. Biometrika 85, 103-114.
Bing Li (2000). Nonparametric estimating equations based on a Penalized Information Criterion. Canadian Journal
of Statistics, 28, 621-639.
Annie Qu, Bruce Lindsay, and Bing Li (2000). Improving generalized estimating equations using quadratic inference functions.
Biometrika 87, page 823-836.
Bing Li (2000). Comment on `On Profile Likelihood' by S. A. Murphy and A. W. van der Vaart. Journal of the American
Statistical Association 95, 472-473.
Bing Li (2000). Comment on `Eliminating multiple roots problems in estimation' by Small, Wang, and Yang. Statistical
Science. 15, 336-339.
Journal of Statistical Planning and Inference, 97, 57-66.
Bing Li (2001). On quasilikelihood equations with nonparametric weights. Scandinavian Journal of Statistics,
Xiaotong Shen and Bing Li (2001). Comment on `Inference for semiparametric models: some current frontiers' by
Peter J. Bickel and Jaimyoung Kwon. Statistics Sinica. 11, 936-940.
R. Dennis Cook and Bing Li (2002). Dimension reduction for conditional mean in regression. The Annals of Statistics.
Francesca Chiaromonte, Dennis Cook, and Bing Li (2002). Partial dimension reduction with categorical predictors.
The Annals of Statistics. 30, 475-497.
Bing Li, R. Dennis Cook, and Francesca Chiaromonte (2003). Dimension reduction for conditional mean in regression with
categorical predictors. The Annals of Statistics. 31, 1636-1668
R. Dennis Cook and Bing Li (2004). Determining the dimension of iterative Hessian transformation.
The Annals of Statistics. 32, 2501-2531.
Bing Li, Hongyuan Zha, Francesca Chiaromonte (2005).
Contour regression: a general approach to dimension reduction. The Annals of Statistics. 33, 1580-1616.
Bing Li and Xiangrong Yin (2007). Surrogate dimension reduction for measurement error regression: An invariance law.
The Annals of Statistics. 35, 2143-2172.
R. Dennis Cook, Bing Li, and Francesca Chiaromonte (2007). Dimension reduction without matrix inversion. Biometrika.
Bing Li and Shaoli Wang (2007). On directional regression for dimension reduction. Journal of American
Statistical Association. 102, 997-1008.
Bing Li (2007). Comment on Fisher Lecture: Dimension Reduction in Regression by R. Dennis Cook.
Statistical Science. 22, 32-35.
Xiangrong Yin, Bing Li, and Dennis Cook (2008). Successive direction extraction for estimating the central
Subspace in a multiple-index regression. Journal of Multivariate Analysis. 99, 1733 - 1757.
Abram Kagan and Bing Li (2008). An identity for the Fisher information and Mahalanobis distance. Journal of Statistical Planning and Inference. 138 3950-3959.
Bing Li, Songqiao Wen, and Lixing Zhu (2008). On a Projective Resampling method for dimension reduction with multivariate responses. Journal of American Statistical Association. 103, 1177 - 1186.
Andreas Artemiou and Bing Li (2009). On principal components and regression: a statistical explanation of a natural phenomenon. Statistica Sinica. 19, 1557-1566.
Bing Li and Yuexiao Dong (2009). Dimension reduction for non-elliptically distributed predictors.
The Annals of Statistics.37, 1272-1298.
Yuexiao Dong and Bing Li (2010). Dimension reduction for non-elliptically distributed predictors: second-order methods. Biometrika. 97, 279 - 294.
Bing Li, Min Kyung Kim, and Naomi Altman (2010). On dimension folding of matrix or array valued statistical objects. The Annals of Statistics. 38, 1097 - 1121.
R. Dennis Cook, Bing Li, and Francesca Chiaromonte (2010). Envelope models for parsimonious and efficient multivariate linear regression (with discussion). Statistica Sinica. 20, 927-1010.
Lexin Li, Bing Li, and Lixing Zhu (2010). Groupwise dimension reduction. Journal of American Statistical Association. 105, 1188 - 1201.
Xiangrong Yin and Bing Li (2011). Sufficient dimension reduction based on an ensemble of minimum average variance estimators. The Annals of Statistics. 39, 3392 - 3416.
Bing Li, Andreas Artemiou, and Lexin Li (2011). Principal support vector machines for linear and nonlinear sufficient dimension reduction. The Annals of Statistics. 39, 3182-3210.
Bing Li, Hyonho Chun, and Hongyu Zhao (2012). Sparse estimation of conditional graphical models with application to gene networks. To appear in Journal of American Statistical Association.