Gaussian processes and random differential equations

 

  1. Xiaoou Li, Jingchen Liu, Jianfeng Lu, and Xiang Zhou. Moderate Deviation for Random Elliptic PDE with Small Noise. The Annals of Applied Probability. Accepted.
  2. Xiaoou Li, Jingchen Liu, Gongjun Xu. On the Tail Probabilities of Aggregated Lognormal Random Fields with Small Noise. Mathematics of Operations Research, 41(1), 236-246, 2016.
  3. Xiaoou Li and Jingchen Liu. Rare-event Simulation and Efficient Discretization for the Supremum of Gaussian Random Fields. Advances in Applied Probability, 47(3), 787-816, 2015.
  4. Jingchen Liu, Jianfeng Lu, and Xiang Zhou. Efficient Rare-event Simulation for Failure Problems in Random Media. SIAM Journal on Scientific Computing. 37(2), A609-A624, 2015.
  5. Gongjun Xu, Guang Lin, and Jingchen Liu. Rare-event Simulation for Stochastic Korteweg-de Vries Equation. SIAM/ASA Journal on Uncertainty Quantification, 2(1), 698-716, 2014.
  6. Jingchen Liu and Gongjun Xu. On the Conditional Distributions and the Efficient Simulations of Exponential Integrals of Gaussian Random Fields. Annals of Applied Probability, 24(4), 1691-1738, 2014.
  7. Jingchen Liu and Xiang Zhou. Extreme Analysis of a Random Ordinary Differential Equation. Journal of Applied Probability, 51(4), 2014. Supplemental materials. A long version.
  8. Jingchen Liu and Gongjun Xu. On the Efficient Simulations for the Exponential Integrals of General H\"older Continuous Gaussian Random Fields. The ACM Transactions on Modeling and Computer Simulation. 24(2), 1-24, 2014.
  9. Jingchen Liu and Gongjun Xu. On the Density Functions of Integrals of Gaussian Random Fields. Advances in Applied Probability, 45(2), 398-424, 2013.
  10. Jingchen Liu and Xiang Zhou (2013). On the Failure Probability for One Dimensional Random Material under delta External Force. Communications in Mathematical Sciences. 11(2), 499-521.
  11. Jingchen Liu and Gongjun Xu (2012). Some Asymptotic Results of Gaussian Random Fields with Varying Mean Functions and the Associated Processes. Annals of Statistics, 40(1), 262-293. arXiv
  12. Robert J. Adler, Jose H. Blanchet and Jingchen Liu (2012). Efficient Monte Carlo for High Excursions of Gaussian Random Fields. Annals of Applied Probability, 22(3), 1167-1214. presentation video
  13. Jingchen Liu (2012). Tail Approximations of Integrals of Gaussian Random Fields. Annals of Probability, 40(3), 1069 - 1104.

 

Psychometrics

 

  1. Yunxiao Chen, Xiaoou Li, Jingchen Liu, Zhiliang Ying. Robust Measurement via A Fused Latent and Graphical Item Response Theory Model. Psychometrika. To appear.
  2. Haochen Xu, Guanhua Fang, Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. Latent Class Analysis of Recurrent Events in Problem-Solving Items. Applied Psychological Measurements. To appear.
  3. Yunxiao Chen, Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Recommendation System for Adaptive Learning. Applied Psychological Measurements, 42(1), 2018.
  4. Yunxiao Chen, Xiaoou Li, Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Exploratory Item Classification via Spectral Graph Clustering. Applied Psychological Measurement, 41(8), 579-599, 2017.
  5. Yunxiao Chen, Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Regularized Latent Class Analysis with Application in Cognitive Diagnosis. Psychometrika, 82(3), 660-692, 2017.
  6. Jingchen Liu. On The Consistency of Q-matrix Estimation - A Commentary. Psychometrika, 82(2), 523-527, 2017.
  7. Jianan Sun, Yunxiao Chen, Jingchen Liu, Zhiliang Ying, and Tao Xin. Latent Variable Selection for Multidimensional Item Response Theory Models via L_1 Regularization. Psychometrika, 81(4), 921-939, 2016.
  8. Yeojin Chung, Andrew Gelman, Sophia Rabe-Hesketh, Jingchen Liu, and Vincent Dorie. Weakly Informative Prior for Point Estimation of Covariance Matrices in Hierarchical Models. Journal of Educational and Behavioral Statistics. 40(2), 136-157, 2015.
  9. Jingchen Liu, Zhiliang Ying, and Stephanie Zhang. A Rate Function Approach to the Computerized Adaptive Testing for Cognitive Diagnosis. Psychometrika, 80(2), 468-490, 2015.
  10. Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. Online Item Calibration for Q-matrix in CD-CAT. Applied Psychological Measurement. 39(1), 5-15, 2015.
  11. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Theory of Self-learning Q-matrix. Bernoulli, 19(5A), 1790-1817, 2013.
  12. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Data-driven Learning of Q-matrix. Applied Psychological Measurement. 36(7), 609 - 618, 2012.

 

Heavy-tailed processes

 

  1. Jingchen Liu and Jae-Kyung Woo. Asymptotic Analysis of Risk Quantities Conditional on Ruin For Multidimensional Heavy-tailed Random Walks. Insurance: Mathematics and Economics, 55, 1-9, 2014.
  2. Jose H. Blanchet and Jingchen Liu. Total Variation Approximation of High Dimensional First Passage Time Problems. Bernoulli, 20(2), 416-456, 2014.
  3. Jose H. Blanchet and Jingchen Liu (2012).  Efficient Simulation and Conditional Functional Limit Theorems for Ruinous Heavy-tailed Random Walks. Stochastic Processes and Their Applications, 122(8), 2994-3031.
  4. Jose H. Blanchet and Jingchen Liu (2010). Efficient Importance Sampling in Ruin Problems for Multidimensional Regularly Varying Random Walks . Journal of Applied Probability, 47, 301 - 322.
  5. Jose H. Blanchet and Jingchen Liu (2008). State-dependent Importance Sampling for Regularly Varying Random Walks. Advances in Applied Probability, 40, 1104 - 1128.
  6. Jose H. Blanchet, Peter W. Glynn and Jingchen Liu (2007). Fluid Heuristics, Lyapunov Bounds and Efficient Importance Sampling for a Heavy-tailed G/G/1 Queue. Queueing Systems - Theory and Applications, 57, 99 - 113.

 

Other topics (mostly statistics)

 

  1. Angela Huyue Zhang, Jingchen Liu, and Nuno Garoupa. Judging in Europe: Does Legal Tradition Matter? Journal of Competition Law and Economics. To appear.
  2. Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Chernoff Index for Cox Test of Separate Parametric Families. The Annals of Statistics, 46(1), 1-29, 2018.
  3. Shang Li, Xiaoou Li, Xiaodong Wang, and Jingchen Liu. Decentralized Sequential Composite Hypothesis Test Based on One-bit Communication. IEEE Transactions on Information Theory, 63(6), 3405 - 3424, 2017.
  4. Margarita Alegria, Robert E. Drake, Hyeon-Ah Kang, Justin Metcalfe, Jingchen Liu, Karissa DiMarzio, and Naomi Ali. Simulations Test Impact of Education, Employment, And Income Improvements On Minority Patients With Mental Illness. Health Affairs, 36(6), 1024-1031, 2017.
  5. Yunxiao Chen, Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Statistical Analysis of Q-matrix Based Diagnostic Classification Models. Journal of the American Statistical Association, 110(510), 850-866, 2015.
  6. Xiaoou Li, Jingchen Liu, and Zhiliang Ying (2014). Generalized Sequential Probability Ratio Test. Sequential Analysis, 33, 539-563.
  7. Xiaodong Li, Jingchen Liu, Naihua Duan, Ragy Girgis, Huiping Jiang and Jeffrey Lieberman (2014). A Multiple Imputation Approach for Drop-out in Longitudinal Studies. Statistics in Medicine. 33(12), 2030-2047.
  8. Jingchen Liu, Xiao-Li Meng, Margarita Alegria and Chih-nan Chen (2013). Statistics Can Lie But Can Also Correct for Lies: Reducing Response Bias in NLAAS via Bayesian Imputation. Statistics and Its Interface, 6(3), 387-398.
  9. Jingchen Liu, Andrew Gelman, Jennifer Hill and Yu-Sung Su. On the Stationary Distribution of the Iterative Imputations. Biometrika. 101(1), 155-173, 2014. Supplemental materials.
  10. Yeojin Chung, Sophia Rabe-Hesketh, Andrew Gelman, Vincent Dorie, and Jingchen Liu. A Non-degenerate Estimator for Variance Parameters in Multilevel Models via Penalized Likelihood Estimation. Psychometrika. 78, 685-709, 2013.
  11. Jingchen Liu and Xuan Yang. The Convergence Rate and Asymptotic Distribution of Bootstrap Quantile Variance Estimator for Importance Sampling. Advances in Applied Probability, 44(3), 815-841, 2012.
  12. Richard A. Davis and Jingchen Liu (2011). Discussion to "A Statistical Analysis of Multiple Temperature Proxies" by Blackely B. McShane and Abraham J. Wyner, Annals of Applied Statistics, 5, 52 - 55.

 

Submitted

 

  1. Xiaoou Li, Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. A Fused Latent and Graphical Model for Multivariate Binary Data.

 

Refereed Conference Proceedings

 

  1. Jingchen Liu and Gongjun Xu (2012). Rare-event Simulation for Exponential Integrals of Smooth Gaussian Processes. Proceedings of the 2012 Winter Simulation Conference.
  2. Jingchen Liu, Xiang Zhou, Rohit Patra, and Weinan E (2011). Failure of Random Materials: A Large Deviation and Computational Study. Proceedings of the 2011 Winter Simulation Conference.
  3. Jose H. Blanchet, Jingchen Liu, and Xuan Yang (2010). Monte Carlo for Large Credit Portfolios with Potentially High Correlations.  Proceedings of the 2010 Winter Simulation Conference.
  4. Robert J. Adler, Jose H. Blanchet and Jingchen Liu (2008).  Efficient Simulation for Tial Probabilities of Gaussian Random Fields. Proceedings of the 2008 Winter Simulation Conference.
  5. Jose H. Blanchet, Jingchen Liu, and Zwart, Bert (2008). Large Deviations Perspective on Ordinal Optimization of Heavy-tailed Systems. Proceedings of the 2008 Winter Simulation Conference.
  6. Jose H. Blanchet, Jingchen Liu (2007). Rare-event Simulation for A Multidimensional Random Walk with t Distribution Increments. Proceedings of the 2007 Winter Simulation Conference.
  7. Jose H. Blanchet, Jingchen Liu (2007). Path-sampling for State-dependent Importance Sampling. Proceedings of the 2007 Winter Simulation Conference.
  8. Jose H. Blanchet, Jingchen Liu and Peter W. Glynn (2006).  State-dependent Importance Sampling and Large Deviations. Proceedings of the 1st International Conference on Performance Evaluation Methodologies and Tools.
  9. Jose H. Blanchet, Jingchen Liu (2006). Efficient Simulation for Large Deviation Probabilities of Sums of Heavy-tailed Increments. Proceedings of the 2006 Winter Simulation Conference.

 

Other Publications

 

  1. Jingchen Liu (2008). Effective modeling and scientific computation with applications to health study, astronomy, and queueing network. Doctoral Dissertation, Harvard University.
  2. Jingchen Liu, Xiao-Li Meng, Margarita Alegria and Chih-nan Chen (2006). Multiple Imputation for Response Biases in NLAAS Due to Survey Instruments. ASA Proceedings of the Joint Statistical Meetings.
  3. Xiao-Li Meng, Margarita Alegria, Chih-nan Chen and Jingchen Liu (2005). A Nonlinear Hierarchical Model for Estimating Prevalence Rates with Small Samples. ASA Proceedings of the Joint Statistical Meetings, 110-120, American Statistical Association (Alexandria, VA).

 

Technical Reports (If you are interested in the following papers, please send me an email!)

 

  1. Hyeon-Ah Kang, Jingchen Liu, and Zhiliang Ying. Graphical Diagnostic Classification Model.
  2. Brian Ling, Guanhua Fang, Jingchen Liu, and Zhiliang Ying. Dirichlet Allocated Latent Class and Graphical Model.
  3. Jose H. Blanchet, Peter W. Glynn and Jingchen Liu. Efficient Rare Event Simulation for Heavy-tailed Multiserver Queues.
  4. Henrik Hult, Jingchen Liu, and Xuan Yang. Self-learning Markov Chain Monte Carlo from a Large Deviations Point of View.