Professor Xuewen Lu

More Information

Book

• McKellar, Robin and Lu, Xuewen. Modeling Microbiology Food Responses CRC PRESS, 2003. Print.

Forthcoming

• Broken adaptive ridge method for variable selection in generalized partly linear models with application to the coronary artery disease data. Journal of Computational Mathematics and Data Science, accepted, arXiv preprint arXiv:2311.00210

   

Journal article

STATISTICAL JOURNAL PAPERS:

• Cai*, K., Lu, X., and Shen, H.  (2025). Group sparse sufficient dimension reduction: a model-free group variable selection method. Computational Statistics, 40 (5), 2323-2366, https://doi.org/10.1007/s00180-024-01547-5         [Q2].
• Yang, J., Tian, G., Lu, X. , and Wang, M. (2025). Robust model structure for ultra-high-dimensional varying-coefficient models. Communications in Mathematics and Statistics, 13 (3), 757-787,  DOI: https://doi.org/10.1007/s40304-023-00336-8 [Q3].
• Mahmoudi, F. and Lu, X. (2025). Penalized variable selection with broken adaptive ridge regression for semi-competing risks data. Journal of Nonparametric Statistics, 1-36, https://doi.org/10.1080/10485252.2025.2475778     [Q3].
• Cai*, K., Shen, H., & Lu, X. (2024). Variable selection and estimation for recurrent event model with covariates subject to measurement error. Journal of Statistical Computation and Simulation, 94, 3633-3652.   [Q2].
• Zhang, C., Huang, H., Bandyopadhyay, D., Al-Mosawi, R. R., & Lu, X. (2024). Sieve Estimation of the Additive Hazards Model with Bivariate Current Status Data. Statistics in Biosciences, 17, 251-206. https://doi.org/10.1007/s12561-024-09436-7  [Q3].
• Chan, C., Mahmoudi, F., Lee, C-H.,  Long, Q. and Lu, X. (2024). Variable selection in the joint frailty model of recurrent and terminal events using Broken Adaptive Ridge regression. arXiv preprint arXiv:2409.00291, under revision of Journal of Statistical Planning and Inference. [Q2].
• Liao, Y., Hua*, J., Luo, L., Ping, W., Lu, X., & Zhong, Y. (2024). APRCOIE: An open information extraction system for Chinese. SoftwareX, 26, 101649.  [Q3].
• Dai*, X., Acosta, N., Lu, X., Hubert, C. R., Lee, J., Frankowski, K., ... & Chekouo, T. (2024). A Bayesian framework for modeling COVID‐19 case numbers through longitudinal monitoring of SARS‐CoV‐2 RNA in wastewater. Statistics in Medicine. 2024, 43:1153–1169.  [Q1].
• Lu, F., Liu, S., Yang, J. and Lu, X. (2023). Automatic variable selection for semiparametric spatial autoregressive model. Econometric Reviews, 42, 655-675. [Q1] SJR (Scimago Journal and Country Rank).
• Lu F, Yang J, Lu X. Automatic Structure Identification of Semiparametric Spatial Autoregressive Model Based on Smooth-Threshold Estimating Equation[J]. Communications in Mathematics and Statistics, 2023: 1-26.
• Dai*, X. , Lu, X.  and Chekouo, T. (2023). A Bayesian genomic selection approach incorporating prior feature ordering and population structures with application to coronary artery disease, Statistical Methods in Medical Research. 32, 1616-1629. [Q1] SJR (Scimago Journal and Country Rank).
• Lu, F., Huang X., Lu, X. Tian, G. and Yang, J. (2023). Model detection for semiparametric accelerated failure additive model with right-censored data, Statistical Methods in Medical Research. 32, 1527-1542. [Q1].
• Chan, C., Dai, X. Chekouo, T., Long, Q. and Lu, X. (2023). Broken adaptive ridge method for variable selection in generalized partly linear models with application to the coronary artery disease data. Under revision of Journal of Computational Mathematics and Data Science, arXiv preprint arXiv:2311.00210 [Q3].
• Lu, X, Wang*, Y., Bandyopadhyay, D., and Bakoyannis, G. (2023).  Sieve estimation of a class of partially linear transformation models with interval-censored competing risks data. Statistica Sinica, 33, 685-704. [Q1].
• Cai*, K., Shen, H. and Lu, X. (2022). Adaptive bi-level variable selection for multivariate failure time model with a diverging number of covariates.  Test, 31, 968-993. [Q2].
• Lu, F., Yang, J., and Lu, X. (2022). One-step oracle procedure for semi-parametric spatial autoregressive model and its empirical application to Boston housing price data. Empirical Economics, 62(6), 2645-2671. [Q2].
• Al-Mosawi, R. and Lu, X. (2022). Efficient estimation of semiparametric varying-coefficient partially linear transformation model with case-I interval censored data. Journal of Statistical Computation and Simulation. 92, 416-435. [Q2].
• Zhang*, M., Lu, X., Hoffman, E., Kharabsheh, R., and Xiao, Q. (2021a). Radioactive source search problem and optimisation model based on meta-heuristic algorithm. Applied Mathematics and Nonlinear Sciences, 7(2), 601-630. [Q2].
• Fani*, S., Shen, H., Lu, X. and Wu, J. (2021). Semiparametric regression with the U-shaped baseline hazard function in the additive hazards model.  Journal of Statistical Computation and Simulation. 91, 3255-3282. [Q2].
• Wu, J., Lu, X. and Zhong*, W.  (2021). Bi-level variable selection in semiparametric transformation mixture cure models for right-censored data. Communications in Statistics - Simulation and Computation. Accepted. https://doi.org/10.1080/03610918.2021.1926499       [Q3].
• Afzal*, A., Yang, J. and Lu, X. (2021). Variable Selection in Partially Linear Additive Hazards Model with Grouped Covariates and a Diverging Number of Parameters. Computational Statistics. 36, 829-855. [Q2].
• Cai*, K., Shen, H. and Lu, X. (2021). Group Variable Selection for Recurrent Event Model with a Diverging Number of Covariates. Statistics and Its Interface. 14, 431-447.  [Q3].
• Zhong*, W., Lu, X. and Wu, J. (2021). Bi-level Variable Selection in Semiparametric Transformation Models with Right- censored Data. Computational Statistics. 36, 1661-1692. . [Q2]
• Huang*, L., Kopciuk, K. and Lu, X. (2021). A group bridge approach for component selection in nonparametric accelerated failure time additive regression model. Communications in Statistics-Theory and Methods. 50, 1447-1501. https://doi.org/10.1080/03610926.2019.1651861 [Q3]. (Above will be used in the biennual appraisal of 2021-2023).
• Huang, H.  and Lu, X. (2020). On complete moment convergence for weighted sums of negatively superadditive dependent random variables. Applications of Mathematics.  4, 355-377. [Q4].
• Huang, H., Li, L. and Lu, X. (2020). Convergence of the tail probability for weighted sums of negatively orthant dependent random variables.  Kybernetika.  56, 646-661. [Q4].
• Cai*, K., Shen, H. and Lu, X. (2020). Group variable selection in the Andersen–Gill model for recurrent event data. Journal of Statistical Planning and Inference.  207, 99-112. [SCI] . [Q2].
• Huang*, L., Kopciuk, K., and Lu, X. (2020). Adaptive group bridge selection in the semiparametric accelerated failure time model. Journal of Multivariate Analysis, 175, 104562, online.  . [Q1].
• Yang, J., Lu, F., Lu, X. (2020). Robus check loss-based inference of semiparametric models and its application in environmental data. Journal of Computational and Applied Mathematics, 365, 112267. [Q2].
• Yang, J., Tian, G., Lu, F., and Lu, X. (2020). Single-index modal regression via outer product gradients. Computational Statistics & Data Analysis, 144, 1-14 (106867, online). [Q2].
• Yang, J. Q., Dong*, Y., Singh, R., Dong, C., and Lu, X. (2020). Efficient estimation of a varying-coefficient partially linear proportional hazards model with current-status data. Journal of Statistical Computation and Simulation, 90(1), 90-111. [Q2].
• Huang*, L., Kopciuk, K. and Lu, X. (2019). A group bridge approach for component selection in nonparametric accelerated failure time additive regression model. Communications in Statistics-Theory and Methods. 1-25, Accepted.  https://doi.org/10.1080/03610926.2019.1651861 [Q3].     (Above will be used in the biennual appraisal of 2019-2021).
• Yang, J., Lu, F., Tian, G., Lu, X. and Yang, H. (2019). Robust variable selection of varying coefficient partially nonlinear model based on quantile regression. Statistics and Its Interface, 12(3), 397-413. [Q3].
• Lu*, S., Wu, J. and Lu, X. (2019).  Efficient estimation of the varying-coefficient partially linear proportional odds model with current status data. Metrika. 82, 173-194. [SCI]
• Cheng, T.-L., Lin, Y.-Y., Lu, X., Singh, R.  (2019). On partially linear single-index models with missing response and error-in-variable predictors. Journal of Statistical Theory and Applications. 18, 46-64.
• Huang*, L., Kopciuk, K. and Lu, X. (2018). Smoothed jackknife empirical likelihood for weighted rank regression with censored data. Biostatistics and Biometrics – Open Access Journal. 6(2): 555685. DOI: 10.19080/BBOAJ.2018.06.555685
• Liu, W., Fang, J. and Lu, X. (2018). Additive-Multiplicative hazards model with current status data. Computational Statistics. 33, 1245-1266. [SCI]
• Fang, J., Liu, W. and Lu, X. (2018). Empirical likelihood for heteroscedastic partially linear single-index models with growing dimensional data. Metrika. 81, 255-281. [SCI]
• Pordeli*, P. and Lu, X. (2018).  Efficient estimation of partially linear single-index additive hazards model with current status data. Journal of Statistical Computation and Simulation. 88, 935-966. [SCI]
• Afzal*, A., Dong, C. and Lu, X. (2017). Estimation of partly linear additive hazards model with left-truncated and right-censored data. Statistical Modelling.  17, 1-26. [SCI]
• Fang, J., Liu, W. and Lu, X. (2017). Penalized empirical likelihood for the additive hazards model with high-dimensional data. Journal of Nonparametric Statistics.  29, 326-345. [SCI]
• Fang, J., Liu, W. and Lu, X. (2017). Two-sample high-dimensional empirical likelihood. Communications in Statistics-Theory and Methods. 46, 6323-6335. [SCI]
• Fang, J., Liu, W. and Lu, X. (2017). Penalized empirical likelihood for semiparametric models with a diverging number of parameters. Journal of Statistical Planning and Inference.  186, 42-57. [SCI]
• Zhong*, W., Lu, X. and Wu, J. (2017). Feature selection for cancer classification using microarray gene expression data. Biostatistics and Biometrics – Open Access Journal. 1(2): 555558.
• Lu, X., Pordeli*, P., Burke, M. and Song, P. X.-K. (2016). Partially linear single-index proportional hazards model with current status data. Journal of Multivariate Analysis. 151, 14-36. [SCI].
• Zhang*, Y., Lu, X. and Desmond, A.F. (2016). Variable selection in a log-linear Birnbaum-Saunders regression model for high-dimensional survival data via the elastic-net and stochastic EM. Technometrics.  58, 383-392.   [SCI]
• Liu, W., Lu, X. and Xie, C. (2016).  Empirical likelihood for additive hazards models with current status data. Communications in Statistics - Simulation and Computation. 45, 2720-2732. DOI: 10.1080/03610918.2014.920879.  [SCI]
• Sewalem, A., Desmond, A.F., Singh, R.S. and Lu, X. (2015). Analysis of calf survival data using a partially linear single-index model.  Journal of the Indian Society of Agriculture Statistics. 69, 149-160.
• Lu, X. , Song, P. X.-K. (2015).  Efficient sieve estimation of the partly linear additive hazards regression model with current status data. Scandinavian J. Statistics. 42, 306-328. DOI: 10.1111/sjos.12108. [SCI]
• Zhu*, Y., Wu, J. and Lu, X. (2013). Minimum Hellinger distance estimation for a two-sample semiparametric cure rate model with censored survival data. Computational Statistics. 28, 2495-2518. [SCI]
• Xie, C., Lu, X., Pogue, J. and Chen, D. (2013). Weighted multiple testing correction for correlated binary endpoints. Communications in Statistics - Simulation and Computation. 42, 1693-1702. [SCI]
• Liu, W., Lu, X. and Qi, Y. (2013).  On local polynomial modelling of the additive risk model. Communications in Statistics-Theory and Methods. 42, 1958-1981. [SCI]
• Yang, J.-Q., Liu, W. and Lu, X. (2012). Local linear estimators of the conditional variance function under random censorship. Quantitative Bio-Science. 31, 101-112.
• Xie, C., Lu, X. and Pogue, J. (2012). Attributable risk function with clustered survival data. Journal of Biometrics and Biostatistics. S1:007. doi:10.4172/2155-6180.S1-007.
• Cheng*, T.-L., Lu, X., Singh, R.S. and Wang, S.Y. (2012). On estimating conditional heteroskedastic models using empirical likelihood estimations. International Journal of Intelligent Technologies and Applied Statistics. 5, 201-216.
• Lu, X., Lian, H. and Liu, W. (2012). Semiparametric estimation for inverse density weighted expectations when responses are missing at random. Journal of Nonparametric Statistics.  24, 139-152. [SCI]
• Ding*, H., Lu, X. and Pan, L. (2012).  A statistical study on the factors influencing CSR disclosure of listed companies in China. Advances and Applications in Statistics. 27, 65-79.
• Lu, X. and Song, P. X.-K. (2012). On efficient estimation in additive hazards regression with current status data. Computational Statistics and Data Analysis. 56, 2051-2058. [SCI]
• Desmond, A.F., Cintora Gonzalez, C.L., Singh, R.S. and Lu, X. (2012). A mixed effects log-linear model for the Birnbaum-Saunders distribution. Computational Statistics and Data Analysis.56, 399-407.  [SCI]
• Liu, W., Lu, X. and Xie, C. (2012). Semiparametric estimation for weighted average derivatives with responses missing at random. Journal of Statistical Planning and Inference. 142, 347-357.  [SCI]
• Ding*, H. and Lu, X. (2011).  Empirical analysis of impact of conversion of convertible bonds on corporate performance of different industries in China. American Open Journal of Statistics.1, 110-114.
• Liu, W. and Lu, X. (2011).  Empirical likelihood for density-weighted average derivatives. Statistical Papers. 52, 391-412. [SCI]
• Lu, X., Nan, B., Song, P. X.-K. and Sowers, M. R. (2010). Longitudinal data analysis with event time as a covariate. Statistics in Biosciences. 2, 65-80. [SCI]
• Cheng*, T.L. Lue, H.H., Lu, X. and Sun, J.W. (2010). Censored regression with error-prone predictors for partially linear single-index models. Journal of Chinese Statistical Association. 48, 108-126.
• Xiao, Q., Liu, Z., Balakrishnan, N. and Lu, X. (2010).  Estimation of the Birnbaum-Saunders regression model with current status data. Computational Statistics and Data Analysis.54, 326-332.  [SCI]
• Lu. X. (2010). Asymptotic distributions of two “synthetic data” estimators for censored single-index models.  Journal of Multivariate Analysis. 101, 999-1015. [SCI]
• Hsieh, H.-N., Su, H.-Y. and Lu, X. (2009). A generalized inference on assessment of similarity between dissolution profiles. Advances and Applications in Statistics.  12, 163-190. (In MathSciNet)
• Yang, J.-Q., Lu, X. and Singh, R.S. (2009). Estimation for two-sample location-scale models under Type I censorship. Communications in Statistics-Theory and Methods. 39, 1932-1950. [SCI]
• Liu, W. and Lu, X. (2009).  Weighted least squares method for censored linear models. Journal of Nonparametric Statistics.  21, 787-799. [SCI]
• Lu, X.  (2009). Empirical likelihood for heteroscedastic partially linear models. Journal of Multivariate Analysis. 100, 387–396. [SCI]
• Sun*, J., Kopciuk, K.A. and Lu, X. (2008).   Polynomial spline estimation of partially linear single-index proportional hazards regression models. Computational Statistics and Data Analysis. 53, 176-188. [SCI]
• Lu, X. and Burke, M.D. (2008). Nonparametric estimation of linear functionals of a bivariate distribution under univariate censoring. Journal of Statistical Planning and Inference. 138, 3238-3256.  [SCI]
• Xie, C., Singh, R.S., Desmond, A.F., Lu, X. and Ormsby, E. (2008). Hierarchical quasi-likelihood approach to bioavailability and bioequivalence analysis. Communications in Statistics-Theory and Methods. 37, 1641-1658. [SCI]
• Cheng*, T.L., Ho, H.C. and Lu, X. (2008).  Asymptotic normality of kernel estimations for linear random fields on Z². Journal of Theoretical Probability. 21, 267-286. [SCI]
• Desmond, A.F., Rodríguez-Yam, G.A. and Lu, X. (2008).  Estimation of parameters for a Birnbaum-Saunders regression model with censored data. Journal of Statistical Computation and Simulation. 11, 983-997. [SCI]
• Lu, X. , Sun*, J. and Qi, Y. (2008).  Empirical likelihood for average derivatives of hazard regression functions.  Metrika, 67, 93-112. [SCI]
• Cheng*, T.L. and Lu, X. (2007). An efficient algorithm on boundary detection. Journal of Chinese Statistical Association. 45, 372-385.
• Liu, W.R. and Lu, X. (2007). Asymptotical Properties of Sample Versions of Type a Statistical Depth Functions. Journal of Natural Science of Hunan Normal University. 30, 1-5.
• Lu, X. and Cheng*, T.L. (2007).  Randomly censored partially linear single-index models. Journal of Multivariate Analysis, 98, 1895-1922. [SCI]
• Lu, X., Singh, R. S. and Desmond, A. F. (2007). Estimation for location-scale models with censored Data.  Communications in Statistics-Theory and Methods, 36, 1069-1089. [SCI]
• Lu, X. and Qi, Y. (2006). Chover's law of the iterated logarithm for trimmed sums. Sankhyā, 68, 488-502. (In MathSciNet)
• Lu, X. and Qi, Y. (2006). Empirical likelihood for average derivatives. Journal of Nonparametric Statistics. 18, 315-331. [SCI] (In MathSciNet)
• Wang, Z., Desmond, A. F. and Lu, X. (2006). Modified censored moment estimation for the two-parameter Birnbaum-Saunders distribution. Computational Statistics and Data Analysis, 50, 1033-1051.  [SCI] (In MathSciNet)
• Lu, X., Chen, G., Singh, R. S. and Song, P. X.-K. (2006). A class of partially linear single-index survival models. Canadian Journal of Statistics, 34, 97-112. [SCI] (In MathSciNet)
• Lu, X. and Burke, M. D. (2005). Censored multiple regression by the method of average derivatives.  Journal of Multivariate Analysis, 95, 182-205. [SCI] (In MathSciNet)
• Xie, C., Singh, R.S., Smith, B. and Lu, X. (2005). Generalized separation theorems for singular values of a matrix and their applications in canonical correlation analysis. Probability and Mathematical Statistics, 25, 223-229. (In MathSciNet)
• Lu, X. and Qi, Y. (2004). A note on asymptotic distribution of products of sums. Statistics and Probability Letters, 68, 407-413. [SCI] (In MathSciNet)
• Lu, X. and Qi, Y. (2004). Empirical likelihood for the additive risk model. Probability and Mathematical Statistics, 24, 419-431. (In MathSciNet)
• Li, Q., Lu, X. and Ullah, A. (2003). Multivariate local polynomial regression for estimating average derivatives. Journal of Nonparametric Statistics, 15, 607-624. [SCI] (In MathSciNet)
• Lu, X., Singh, R. S. and Desmond, A. F. (2001). A kernel smoothed semiparametric survival model. Journal of Statistical Planning and Inference, 98, 119-135. [SCI] (In MathSciNet)
• Singh, R.S. and Lu, X. (2000). Asymptotic normality of estimators for the parameters in the location-scale models with randomly-censored data. Journal of Statistical Research, 35, 133-141. (In MathSciNet)
• Singh, R.S. and Lu, X. (1999). Nonparametric synthetic data regression estimation for censored survival data. Journal of Nonparametric Statistics, 11, 13-31. [SCI] (In MathSciNet)
• Singh, R.S. and Lu, X. (1998). Large sample theory for estimators of the moments based on ‘synthetic data’ under randomly right-censoring. Applied Statistical Science, III, Nonparametric Statistics and Related Topics, S.E. Ahmed, M. Ahsanullah and B.K. Sinha, Eds., Nova Science Publishers, Inc. Commack, New York. 127-141. (In MathSciNet)
• Liu, Z. and Lu, X. (1997). Root‑N‑consistent semiparametric estimation of partially linear models based on K‑‑NN  method. Econometric Reviews, 16, 411-420. [SCI] (In MathSciNet)
• Lu, X. (1996). Regression function kernel estimation based on synthetic data under random censorship. Chinese Journal of Applied Probability and Statistics,12, 29-36. (In MathSciNet).
• Lu, X. (1995). Almost sure L_1‑‑norm convergence of nonparametric estimation of conditional probability densities of stationary processes. Acta. Sci. Nat. Uni. Norm. Hunan,  18, 10‑15. (In MathSciNet)
• Lu, X. (1995). Asymptotic optimality of CV and GCV criterions in nonparametric regression estimation. (Chinese) Journal of Mathematical Statistics and Applied Probability, 10, 56‑66.
• Lu, X. (1994). Estimation of the parameters in the location‑scale model under randomly right‑censoring. Chinese Journal of Applied Probability and Statistics, 10, 272‑277. (In MathSciNet)
• Lu, X. (1993). Use the methods of CV and GCV to estimate nonparametric regression function. Chinese Journal of Applied Probability and Statistics, 9, 70‑81. (In MathSciNet)

• Lu, X. (1992). The nearest neighbour estimator of nonparametric function for dependent observation. Acta. Sci. Nat. Uni. Norm. Hunan, 15, 199‑205. (In MathSciNet)

   

  BIOLOGICAL AND OTHER APPLIED SCIENCE JOURNAL PAPERS:

• Acosta, N., Dai*, X., Bautista, M. A., Waddell, B. J., Lee, J., Du, K., ... Lu, X. … and Parkins, M. D. (2023). Wastewater-based surveillance can be used to model COVID-19-associated workforce absenteeism. Science of The Total Environment, doi: 10.1016/j.scitotenv.2023.165172, 900, 165172. [Q1].
• Lee, J. and Acosta, N., …Dai*, X., …, Lu, X. … and Parkins, M. D.. (2023). Campus node-based wastewater surveillance enables COVID-19 case localization and confirms lower SARS-CoV-2 burden relative to the surrounding community. Water Research, 244, 120469.  [Q1].
• Acosta, N., Bautista, M. A., Waddell, B. J., Du, K., McCalder, J., ..., Lu, X., …, Dai*, X.,… and Parkins, M. D. (2023). Surveillance for SARS‐CoV‐2 and its variants in wastewater of tertiary care hospitals correlates with increasing case burden and outbreaks. Journal of Medical Virology, 95(2), e28442. [Q1].
• Acosta, N., Bautista, M. A., Waddell, B. J., McCalder, J., Beaudet, A. B., Man, L., ..., Dai*, X., …, Lu, X., … , and Parkins, M. D. (2022). Longitudinal SARS-CoV-2 RNA wastewater monitoring across a range of scales correlates with total and regional COVID-19 burden in a well-defined urban population. Water Research, 220, 118611. [Q1].
• Kossinna*, P., Cai, W., Lu, X., Shemanko, C. S., & Zhang, Q. (2022). Stabilized COre gene and Pathway Election uncovers pan-cancer shared pathways and a cancer-specific driver. Science Advances, 8(51), eabo2846.   [Q1].
• Dai*, X., Champredon, D., Fazil, A., Mangat, C.S., Peterson, S.W., Mejia, E.M., Lu, X. and Chekouo, T., (2022). Statistical framework to support the epidemiological interpretation of SARS-CoV-2 concentration in municipal wastewater. Scientific Reports, 12(1), p.13490. . [Q1].
• Feng*, Y., Leung, A. A., Lu, X., Liang, Z., Quan, H., & Walker, R. L. (2022). Personalized prediction of incident hospitalization for cardiovascular disease in patients with hypertension using machine learning. BMC Medical Research Methodology, 22(1), 1-11. [Q1].
• Zhang*, M., Xu, Z., Lu, X., Liu, Y., Xiao, Q., & Taheri, B. (2021b). An optimal model identification for solid oxide fuel cell based on extreme learning machines optimized by improved Red Fox Optimization algorithm. International Journal of Hydrogen Energy, 46(55), 28270-28281. [Q1].
• Menon, B.K., O’Brien, B., Bivard, A., Spratt, N.J., Demchuk, A.M., Miteff, F., Lu, X., Levi, C. and Parsons, M.W. (2013).  Assessment of leptomeningeal collaterals using dynamic CT angiography in patients with acute ischemic stroke. Journal of Cerebral Blood Flow and Metabolism. 33, 365-371. [SCI] . [Q1].
• Zhong, M., Hunt, J.D. and Lu, X. (2008). Studying differences of household weekday and weekend activities: a duration perspective. Transportation Research Record: Journal of the Transportation Research Board. 2054, 28-36. [SCI]
• Liu, Q.,  Lu, X. and Yada, R. (2005). The effect of various potato cultivars at different times during growth on starch content determined by differential scanning calorimetry. Journal of Thermal Analysis and Calorimetry, 79, 13-18. [SCI]
• McKellar, R.C. and Lu, X. (2005). Development of a global stochastic model describing the relationship between the distribution of individual cell physiological states and population physiological state. International Journal of Food Microbiology, 100, 33-40.  [SCI]
• McKellar, R.C., Rupasinghe, V.H.P., Lu, X. and Knight, K.P. (2005).  The electronic nose as a tool for the classification of fruit and grape wines from different Ontario wineries. Journal of the Science of Food and Agriculture, 85, 2391-2396. [SCI]
• McKellar, R.C., McGarvey, B.D., Tsao, R. , Lu, X. and Knight, K.P. (2005).  Application of the electronic nose to the classification of resistance to Western flower thrips in chrysanthemums. Journal of Chemical Ecology. 31, 2439-2450.  [SCI]
• Vulicevic, I.R., Abdel-Aal, E-S.M., Mittal, G.S. and Lu, X. (2004). Quality and storage life of par-baked frozen breads. Lebensmittel-Wissenschaft und Technologie, 37, 205-213.
• McKellar, R.,  Odumeru, J., Zhou, T.,  Harrison, A.D., Mercer, D.G.,  Young, J.C., Lu, X., Boulter, J., Piyasena, P. and Karr, S. (2004). Influence of a commercial warm chlorinated water treatment and packaging on the shelf-life of ready-to-use lettuce. Food Research International, 37, 343-354. [SCI]
• Zhou, T., Harrison, A.D., McKellar, R., Young, J.C., Odumeru, J., Piyasena, P. and Lu, X., Mercer, D.G. and Karr, S. (2004). Measurement of acceptability and shelf life of ready-to-use lettuce by digital image analysis.  Food Research International, 37, 875-881. [SCI]
• Young, J.C., Chu, C.L.G., Lu, X. and Zhu, H. (2004). Ester variability in apple varieties as determined by solid-phase microextraction and gas chromatography-mass spectrometry. Journal of Agricultural and Food Chemistry, 52, 8086-8093. [SCI]
• Odumeru, J.A., Boulter, J., Knight, K., Lu, X. and McKellar, R.C. (2003). Assessment of a wash treatment with warm chlorinated water to extend the shelf-life of ready-to-use lettuce. Journal of Food Quality, 26, 197-209. [SCI]
• Burgher, K.L., Jamison, A.R. and Lu, X.   (2002). Genetic relationships among lowbush blueberry genotypes as determined by randomly amplified polymorphic DNA analysis.  Journal of the American Society for Horticultural Science, 127, 98-103. [SCI]
• McKellar, R.C., Lu, X. and Knight, K.P. (2002). Proposal of a novel parameter to describe the influence of pH on the lag phage of Listeria monocytogenes.  International Journal of Food Microbiology, 73, 127-135. [SCI]
• McKellar, R.C., Lu, X. and Knight, K.P. (2002). Growth pH does not affect the initial physiological state parameter (p₀) of   listeria monocytogenes. International Journal of Food Microbiology, 73, 137-144. [SCI]
• Yan, W., Hunt, L.A., Johnson, P., Steward, G. and Lu, X. (2002). On-farm strip trials vs. replicated performance trials for cultivar evaluation. Crop Science, 42, 385-392. [SCI]
• Li Wan Po, J.M., Piyasena, P., McKellar, R., Bartlett, F.M., Mittal, G., Lu, X. (2002). Influence of simulated apple cider composition on the heat resistance of Escherichia Coli O157:H7. Lebensmittel‑Wissenschaft und Technologie, 35, 295-304.
• Chambers, J.R. and Lu, X. (2002). Probiotics and maternal vaccination for salmonella control in broiler chickens. Journal of Applied Poultry Research, 11, 320-327. [SCI]
• Zhou, T., Northover, J., Schneider, K.E. and Lu, X. (2002). Interaction between Pseudomonas syringae MA-4 and cyprodinil in the control of blue mold and gray mold of apples. Canadian Journal of Plant Pathology, 24. 154-161. [SCI]
• McKellar, R.C., Young, J.C., Johnston, A., Knight, K.P., Lu, X. and Buttenham, S. (2002). Use of the electronic nose and gas chromatography-mass spectrometry to determine the optimum time for aging of beer. Technical Quarterly, Master Brewers Association of the Americas, 39, 99-105.
• McKellar, R.C., Lu, X., Delaquis, P.J. (2002). A probability model describing the interface between survival and death of Escherichia coli O157:H7 in a mayonnaise model system. Food Microbiology, 19, 235-247. [SCI]
• Reynolds, W.D., Bowman, B.T., Drury, C.F., Tan, C.S., Lu, X. (2002). Indicator of good soil physical quality: density and storage parameters. Geoderma, 110, 131-146. [SCI]
• Hildebrand, P.D., McRae, K.B. and Lu, X. (2001). Factors affecting flower infections and disease severity of lowbush blueberry by Botrytis cinerea. Canadian Journal of Plant Pathology, 23. 364-370. [SCI]
• McKellar, R.C., Lu, X. (2001). A probability growth model for Escherichia coli O157:H7 as a function of temperature, pH, acetic acid, and salt. Journal of Food Protection, 64, 1922-1928. [SCI]
• Atlin, G.N., Baker, R.J., McRae, K.B. and Lu, X.  (2000). The effect of subdividing a target region on selection response. Crop Science, 40, 7-13. [SCI]
• Sturz, A.V., Stewart, J.G., McRae, K.B., Diamond, J.F. Lu, X. and Singh, R.P. (2000). Assessment of the importance of seed cutting, in-season cultivation and the passage of rom equipment in the spread of PVY⁰   in potatoes. Canadian Journal of Plant Pathology, 22, 166‑173. [SCI]
• Hildebrand, P.D., Nickerson, N.L., McRae, K.B. and Lu, X. (2000). Incidence and impact of red leaf disease caused by Exobasidium vaccinii in lowbush blueberry fields in Nova Scotia.  Canadian Journal of Plant Pathology. 22. 364-367. [SCI]
• Atlin, G.N., McRae, K.B. and Lu, X. (2000). Genotype ´ environment interaction for two-row barley yield in Canada. Crop Science, 40, 1-6. [SCI]
• Charmley, E., Savoie, P., McRae, K. B. and Lu, X. (1999). Effects of maceration at mowing on silage conservation, voluntary intake, digestibility and growth rate of steers fed precision chopped or round bale silages. Canadian Journal of Animal Science, 79, 195-202. [SCI]
• Kalt, W., McDonald, J.E., Ricker, R.D. and Lu, X. (1999). Anthocyanin content and profile within and among blueberry species. Canadian Journal of Plant Science, 79, 617‑623.  [SCI]
• Hildebrand, P.D., Braun, K.B., McRae, K.B. and Lu, X. (1998). Role of the biosurfactant viscosin in broccoli head rot caused by a pectolytic strain of Pseudomonas fluorescens. Canadian Journal Plant Pathology, 20, 296-303. [SCI]

STATISTICAL CHAPTERS AND BOOKS:

1. Al-Mosawi, R. R., & Lu, X. (2022). Sieve estimation of semiparametric linear transformation Model with left-truncated and current status data. In Advances and Innovations in Statistics and Data Science (pp. 181-224). Cham, Switzerland Springer International Publishing.
2. Afzal*, A. R. and Lu, X. (2020). Variable selection in partially linear proportional hazards model with grouped covariates and a diverging number of parameters. Book Chapter: In Statistical Modeling in Biomedical Research (pp. 411-448). Springer, Nature.
3. Book: Advanced Statistical Methods in Data Science, edited by Ding-Geng (Din) Chen, Jiahua Chen, Xuewen Lu, Grace Y. Li and Hao Yu Eds. Number of Pages: 229. Springer Singapore, Singapore, 2016.
4. Pordeli, P. and Lu, X. (2016). A proportional odds model for regression analysis of case I interval-censored data. Advanced Statistical Methods in Data Science, 101-122.  Ding-Geng (Din) Chen, Jiahua Chen, Xuewen Lu, Grace Y. Li and Hao Yu Eds. Springer Singapore, Singapore.
5. Huang, L., Kopciuk, K. and Lu, X. (2016). Group selection in semiparametric accelerated failure time model. Advanced Statistical Methods in Data Science, 77-99.  Ding-Geng (Din) Chen, Jiahua Chen, Xuewen Lu, Grace Y. Li and Hao Yu Eds. Springer Singapore, Singapore.
6. Xie, C., Lu, X. and Chen, D.G. (2015). Comparative study of five weighted parametric multiple testing methods for correlated multiple endpoints in clinical trials. Clinical Trial Biostatistics and Biopharmaceutical Applications, 421-432. Walter R. Young and Ding-Geng (Din) Chen Eds., CRC Press, Boca Raton, FL.
7. Lu, X. and Singh, R.S. (2002). Semiparametric location-scale regression models for survival data. Advances on Methodological and Applied Aspects of Probability and Statistics. IISA 199 Conference Proceedings Volume, McMaster University, Hamilton, Ontario, Canada. Vol. I, 305-324. N. Balakrishnan et al., Eds., Taylor and Francis, London.
8. Singh, R.S. and Lu, X. (2002). Censored additive regression models. Handbook of Applied Economics and Statistical Inference. 143-157. Ullah, Wan and Chaturvedi Eds., Marcel Dekker, New York.
9. Lu, X. and Singh, R.S. (2002). One-step estimation for the partially linear proportional hazards model. Recent Advances in Statistical Methods. Proceedings of the 4th Conference in Applied Statistics, Montreal, Canada, 2001. 169-185. Y.P. Chaubey Ed., Imperial College Press, London.
10. Singh, R.S. and Lu, X. (1998). Large sample theory for estimators of the moments based on ‘synthetic data’ under randomly right-censoring. Applied Statistical Science, III, Nonparametric Statistics and Related Topics, 127-141. S.E. Ahmed et al. Eds., Nova Science Publishers, Inc. Commack, New York.

·BIOLOGICAL SCIENCE BOOK CHAPTERS AND BOOKS:

1. Book: Modeling Microbial Responses in Food, edited by McKellar, R.C. and Lu, X., CRC Press, Boca Raton, FL, 2003.
2. McKellar, R.C. and Lu, X. (2003). Development of a global stochastic model describing the relationship between the distribution of individual cell physiological states and population physiological state. Predictive Modelling in Foods Conference Proceedings, Van Impe, J.F.M., Geeraerd, A.H., Leguerinel, I. and Mafart, P. Eds., Katholieke Universiteit Leuven/BioTec, Belgium.
3. McKellar, R.C. and Lu, X. (2003). Primary Models. Modeling Microbial Responses in Food, 21-62. McKellar, R.C. and Lu, X. Eds., CRC Press, Boca Raton, FL.

Preprint

• Cheng, T.-L., Ho, C.H. and Lu, Xuewen. "A note on asymptotic normality of kernel estimations for linear random fields on Z^2". , (2006). Print.
• Lu, Xuewen and Cheng, Tsung-Lin. "Randomly censored partially linear single-index models". , (2006). Print.
• Lu, Xuewen, Sun, Jie and Qi, Yongcheng. "Empirical likelihood for average derivatives of hazard regression functions". , (2006). Print.
• Desmond, A.F., Rodriguez-Yam, G.A. and Lu, Xuewen. "Estimation of parameters for a Birnbaum-Saunders regression model with censored data". , (2005). Print.