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Lianjie Shu, Ph.D. - Publications

Affiliations: 
2002 Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 
Area:
Industrial Engineering
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49 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Fan J, Shu L, Yang A, Li Y. Phase I analysis of high-dimensional covariance matrices based on sparse leading eigenvalues Journal of Quality Technology. 1-14. DOI: 10.1080/00224065.2020.1746212  0.656
2019 Li Y, Liu S, Shu L. Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data Renewable Energy. 134: 357-366. DOI: 10.1016/J.Renene.2018.10.088  0.478
2018 Yang A, Jiang X, Shu L, Liu P. Sparse bayesian kernel multinomial probit regression model for high-dimensional data classification Communications in Statistics - Theory and Methods. 48: 165-176. DOI: 10.1080/03610926.2018.1463385  0.322
2018 Huang W, Shu L, Jiang W. A gradient approach to efficient design and analysis of multivariate EWMA control charts Journal of Statistical Computation and Simulation. 88: 2707-2725. DOI: 10.1080/00949655.2018.1483367  0.422
2018 He F, Mao T, Hu T, Shu L. A new type of change-detection scheme based on the window-limited weighted likelihood ratios Expert Systems With Applications. 94: 149-163. DOI: 10.1016/J.Eswa.2017.10.051  0.36
2018 Shu L, Fan J. A distribution-free control chart for monitoring high-dimensional processes based on interpoint distances Naval Research Logistics (Nrl). 65: 317-330. DOI: 10.1002/Nav.21809  0.336
2017 Fan J, Shu L, Zhao H, Yeung H. Monitoring multivariate process variability via eigenvalues Computers & Industrial Engineering. 113: 269-281. DOI: 10.1016/J.Cie.2017.09.025  0.698
2017 Yang A, Xiang J, Shu L, Yang H. Sparse Bayesian Variable Selection with Correlation Prior for Forecasting Macroeconomic Variable using Highly Correlated Predictors Computational Economics. 51: 323-338. DOI: 10.1007/S10614-017-9741-1  0.333
2016 Huang W, Shu L, Woodall WH, Tsui KL. CUSUM procedures with probability control limits for monitoring processes with variable sample sizes Iie Transactions (Institute of Industrial Engineers). 1-13. DOI: 10.1080/0740817X.2016.1146422  0.361
2016 Li Y, Shu L, Tsung F. A false discovery approach for scanning spatial disease clusters with arbitrary shapes Iie Transactions (Institute of Industrial Engineers). 48: 684-698. DOI: 10.1080/0740817X.2015.1133940  0.63
2016 Huang W, Shu L, Cao J, Tsui KL. Probability distribution of CUSUM charting statistics Iie Transactions (Institute of Industrial Engineers). 1-9. DOI: 10.1080/0740817X.2015.1067736  0.307
2016 Zhou Q, Shu L, Jiang W. One-sided EWMA control charts for monitoring Poisson processes with varying sample sizes Communications in Statistics - Theory and Methods. 45: 6112-6132. DOI: 10.1080/03610926.2014.957853  0.414
2016 Huang W, Shu L, Jiang W. A Gradient Approach to the Optimal Design of CUSUM Charts Under Unknown Mean-Shift Sizes Journal of Quality Technology. 48: 68-83. DOI: 10.1080/00224065.2016.11918152  0.412
2016 Wang G, Su Y, Shu L. One-day-ahead daily power forecasting of photovoltaic systems based on partial functional linear regression models Renewable Energy. 96: 469-478. DOI: 10.1016/J.Renene.2016.04.089  0.332
2016 Li Y, He Y, Su Y, Shu L. Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines Applied Energy. 180: 392-401. DOI: 10.1016/J.Apenergy.2016.07.052  0.501
2016 Yang A, Jiang X, Shu L, Lin J. Bayesian variable selection with sparse and correlation priors for high-dimensional data analysis Computational Statistics. 32: 127-143. DOI: 10.1007/S00180-016-0665-3  0.332
2015 Han SW, Jiang W, Shu L, Tsui KL. A comparison of likelihood-based spatiotemporal monitoring methods under non-homogenous population size Communications in Statistics: Simulation and Computation. 44: 14-39. DOI: 10.1080/03610918.2013.763981  0.398
2014 Shu L, Su Y, Jiang W, Tsui K. A comparison of exponentially weighted moving average-based methods for monitoring increases in incidence rate with varying population size Iie Transactions. 46: 798-812. DOI: 10.1080/0740817X.2014.894805  0.467
2014 Huang W, Shu L, Su Y. An accurate evaluation of adaptive exponentially weighted moving average schemes Iie Transactions. 46: 457-469. DOI: 10.1080/0740817X.2013.803642  0.329
2014 Zhao H, Shu L, Tsui K. A window-limited generalized likelihood ratio test for monitoring Poisson processes with linear drifts Journal of Statistical Computation and Simulation. 85: 2975-2988. DOI: 10.1080/00949655.2014.945933  0.391
2014 Li Y, Su Y, Shu L. An ARMAX model for forecasting the power output of a grid connected photovoltaic system Renewable Energy. 66: 78-89. DOI: 10.1016/J.Renene.2013.11.067  0.488
2014 Shu L, Huang W, Jiang W. A novel gradient approach for optimal design and sensitivity analysis of EWMA control charts Naval Research Logistics (Nrl). 61: 223-237. DOI: 10.1002/Nav.21579  0.481
2013 Shu L, Huang W, Su Y, Tsui K. Computation of the run-length percentiles of CUSUM control charts under changes in variances Journal of Statistical Computation and Simulation. 83: 1238-1251. DOI: 10.1080/00949655.2012.656643  0.332
2013 Jiang W, Shu L, Zhao H, Tsui KL. CUSUM procedures for health care surveillance Quality and Reliability Engineering International. 29: 883-897. DOI: 10.1002/Qre.1444  0.385
2012 Shu L, Jiang W, Wu Z. Exponentially weighted moving average control charts for monitoring increases in Poisson rate Iie Transactions (Institute of Industrial Engineers). 44: 711-723. DOI: 10.1080/0740817X.2011.578609  0.471
2012 Huang W, Shu L, Jiang W. Evaluation of exponentially weighted moving variance control chart subject to linear drifts Computational Statistics and Data Analysis. 56: 4278-4289. DOI: 10.1016/J.Csda.2012.04.013  0.438
2012 Su Y, Chan L, Shu L, Tsui K. Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems Applied Energy. 93: 319-326. DOI: 10.1016/J.Apenergy.2011.12.052  0.301
2012 Shu L, Jiang W, Tsui KL. A standardized scan statistic for detecting spatial clusters with estimated parameters Naval Research Logistics. 59: 397-410. DOI: 10.1002/Nav.21493  0.428
2011 Shu L, Jiang W, Tsui KL. A comparison of weighted CUSUM procedures that account for monotone changes in population size. Statistics in Medicine. 30: 725-41. PMID 21394749 DOI: 10.1002/Sim.4122  0.403
2011 Jiang W, Shu L, Tsui K. Weighted CUSUM Control Charts for Monitoring Poisson Processes with Varying Sample Sizes Journal of Quality Technology. 43: 346-362. DOI: 10.1080/00224065.2011.11917869  0.345
2011 Su Y, Shu L, Tsui K. Adaptive EWMA procedures for monitoring processes subject to linear drifts Computational Statistics & Data Analysis. 55: 2819-2829. DOI: 10.1016/J.Csda.2011.04.008  0.414
2010 Shu L, Yeung H, Jiang W. An Adaptive CUSUM Procedure for Signaling Process Variance Changes of Unknown Sizes Journal of Quality Technology. 42: 69-85. DOI: 10.1080/00224065.2010.11917807  0.356
2009 Wu Z, Khoo MB, Shu L, Jiang W. An np control chart for monitoring the mean of a variable based on an attribute inspection International Journal of Production Economics. 121: 141-147. DOI: 10.1016/J.Ijpe.2009.04.021  0.33
2009 Liu Y, He Z, Shu L, Wu Z. Statistical computation and analyses for attribute events Computational Statistics & Data Analysis. 53: 3412-3425. DOI: 10.1016/J.Csda.2009.02.010  0.317
2008 He F, Jiang W, Shu L. Improved Self-Starting Control Charts for Short Runs Quality Technology & Quantitative Management. 5: 289-308. DOI: 10.1080/16843703.2008.11673402  0.367
2008 Jiang W, Shu L, Apley DW. Adaptive CUSUM procedures with EWMA-based shift estimators Iie Transactions (Institute of Industrial Engineers). 40: 992-1003. DOI: 10.1080/07408170801961412  0.388
2008 Shu L. An adaptive exponentially weighted moving average control chart for monitoring process variances Journal of Statistical Computation and Simulation. 78: 367-384. DOI: 10.1080/00949650601108000  0.421
2008 Shu L, Jiang W. A new EWMA chart for monitoring process dispersion Journal of Quality Technology. 40: 319-331. DOI: 10.1080/00224065.2008.11917737  0.397
2008 Shu L, Jiang W, Tsui K. A Weighted CUSUM Chart for Detecting Patterned Mean Shifts Journal of Quality Technology. 40: 194-213. DOI: 10.1080/00224065.2008.11917725  0.309
2008 Shu L, Jiang W, Wu Z. Adaptive CUSUM procedures with Markovian mean estimation Computational Statistics & Data Analysis. 52: 4395-4409. DOI: 10.1016/J.Csda.2008.02.024  0.344
2007 Shu L, Jiang W, Wu S. A One-Sided EWMA Control Chart for Monitoring Process Means Communications in Statistics - Simulation and Computation. 36: 901-920. DOI: 10.1080/03610910701418465  0.412
2006 Shu L, Jiang W. A Markov Chain model for the adaptive CUSUM control chart Journal of Quality Technology. 38: 135-147. DOI: 10.1080/00224065.2006.11918601  0.382
2006 Jiang W, Shu L, Tsung F. A Comparative Study of Joint Monitoring Schemes for APC Processes Quality and Reliability Engineering International. 22: 939-952. DOI: 10.1002/Qre.780  0.601
2005 SHU L, TSUNG F, TSUI K. Effects of estimation errors on cause-selecting charts Iie Transactions. 37: 559-567. DOI: 10.1080/07408170590929027  0.596
2004 Shu L, Tsung F, Kapur KC. Design of multiple cause-selecting charts for multistage processes with model uncertainty Quality Engineering. 16: 437-450. DOI: 10.1081/Qen-120027945  0.618
2004 Shu L, Tsung F, Tsui K. Run-Length Performance of Regression Control Charts with Estimated Parameters Journal of Quality Technology. 36: 280-292. DOI: 10.1080/00224065.2004.11980274  0.618
2003 Shu L, Tsung F. On Multistage Statistical Process Control Journal of the Chinese Institute of Industrial Engineers. 20: 1-8. DOI: 10.1080/10170660309509217  0.616
2003 Shu L, Tsung F. On multistage statistical process control Journal of the Chinese Institute of Industrial Engineers. 20: 1-8.  0.304
2002 Shu L, Apley DW, Tsung F. Autocorrelated process monitoring using triggered cuscore charts Quality and Reliability Engineering International. 18: 411-421. DOI: 10.1002/Qre.492  0.577
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