References
- Barabási, A.-L., and Albert, R. (1999), “Emergence of Scaling in Random Networks,” Science, 286, 509–512. DOI: https://doi.org/10.1126/science.286.5439.509.
- Bickel, P., Ritov, Y., and Tsybakov, A. (2009), “Simultaneous Analysis of Lasso and Dantzig Selector,” Annals of Statistics, 37, 1705–1732.
- Candes, E., and Tao, T. (2007), “The Dantzig Selector: Statistical Estimation When p is Much Larger Than n,” Annals of Statistics, 35, 2313–2351.
- Chiong, K. X., and Moon, H. R. (2018), “Estimation of Graphical Lasso Using the l1,2 Norm,” Econometrics Journal, 21, 247–263.
- Danaher, P., Wang, P., and Witten, D. M. (2014), “The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes,” Journal of the Royal Statistical Society, 76, 373–397. DOI: https://doi.org/10.1111/rssb.12033.
- Fan, J., Liao, Y., and Liu, H. (2016), “An Overview of the Estimation of Large Covariance and Precision Matrices,” Econometrics Journal, 19, C1–C32. DOI: https://doi.org/10.1111/ectj.12061.
- Gandy, A., and Kvaløy, J. (2013), “Guaranteed Conditional Performance of Control Charts Via Bootstrap Methods,” Scandinavian Journal of Statistics, 40, 647–668. DOI: https://doi.org/10.1002/sjos.12006.
- Gibberd, A. J., and Nelson, J. D. B. (2015), “Regularized Estimation of Piecewise Constant Gaussian Graphical Models: The Group-Fused Graphical Lasso,” Statistics, 1–12.
- Gómez, A., Paynabar, K., and Pacella, M. (2020), “Functional Directed Graphical Models and Applications in Root-Cause Analysis and Diagnosis,” Journal of Quality Technology.
- Guo, J., Levina, E., Michailidis, G., and Zhu, J. (2011), “Joint Estimation of Multiple Graphical Models,” Biometrika, 98, 1–15. DOI: https://doi.org/10.1093/biomet/asq060.
- Jahani, S., Kontar, R., Veeramani, D., and Zhou, S. (2018), “Statistical Monitoring of Multiple Profiles Simultaneously Using Gaussian Processes,” Quality and Reliability Engineering International, 34, 1510–1529. DOI: https://doi.org/10.1002/qre.2326.
- Lauritzen, S. L. (1996), “Graphical Models,” 97, 505–511.
- Li, B., and Solea, E. (2018), “A Nonparametric Graphical Model for Functional Data With Application to Brain Networks Based on fmri,” Journal of the American Statistical Association, 113, 1637–1655. DOI: https://doi.org/10.1080/01621459.2017.1356726.
- Li, H., and Gui, J. (2006), “Gradient Directed Regularization for Sparse Gaussian Concentration Graphs, With Applications to Inference of Genetic Networks,” Biostatistics, 7, 302–317. DOI: https://doi.org/10.1093/biostatistics/kxj008.
- Li, Y., Zhou, Q., Huang, X., and Zeng, L. (2018), “Pairwise Estimation of Multivariate Gaussian Process Models With Replicated Observations: Application to Multivariate Profile Monitoring,” Technometrics, 60, 70–78. DOI: https://doi.org/10.1080/00401706.2017.1305298.
- Meinshausen, N., and Bühlmann, P. (2006), “High-Dimensional Graphs and Variable Selection With the Lasso,” Annals of Statistics, 34, 1436–1462.
- Noorossana, R., Eyvazian, M., Amiri, A., and Mahmoud, M. A. (2010), “Statistical Monitoring of Multivariate Multiple Linear Regression Profiles in Phase I With Calibration Application,” Quality & Reliability Engineering International, 26, 291–303.
- Paynabar, K., Jin, J., and Pacella, M. (2013), “Monitoring and Diagnosis of Multichannel Nonlinear Profile Variations Using Uncorrelated Multilinear Principal Component Analysis,” IIE Transactions, 45, 1235–1247. DOI: https://doi.org/10.1080/0740817X.2013.770187.
- Paynabar, K., Zou, C., and Qiu, P. (2016), “A Change-Point Approach for Phase-I Analysis in Multivariate Profile Monitoring and Diagnosis,” Technometrics, 58, 191–204. DOI: https://doi.org/10.1080/00401706.2015.1042168.
- Peng, J., Wang, P., Zhou, N., and Zhu, J. (2009), “Partial Correlation Estimation by Joint Sparse Regression Models,” Journal of the American Statistical Association, 104, 735–746. DOI: https://doi.org/10.1198/jasa.2009.0126.
- Qiao, X., Guo, S., and James, G. (2019), “Functional Graphical Models,” Journal of the American Statistical Association, 114, 211–222. DOI: https://doi.org/10.1080/01621459.2017.1390466.
- Qiao, X., Qian, C., James, G. M., and Guo, S. (2020), “Doubly Functional Graphical Models in High Dimensions,” Biometrika, 107, 415–431. DOI: https://doi.org/10.1093/biomet/asz072.
- Ramsay, J. O., and Silverman, B. W. (2006), Functional Data Analysis, New York: Springer-Verlag
- Shimamura, T., Imoto, S., Yamaguchi, R., and Miyano, S. (2007), “Weighted Lasso in Graphical Gaussian Modeling for Large Gene Network Estimation Based on Microarray Data,” Genome Informatics. International Conference on Genome Informatics, 19, 142–53.
- Srikanth, R., Tianwen, C., Kaustubh, S., and Vinod, M. (2012), “Estimation of Functional Connectivity in fMRI Data Using Stability Selection-Based Sparse Partial Correlation With Elastic Net Penalty,” Neuroimage, 59, 3852–3861.
- Sun, H., Huang, S., and Jin, R. (2017), “Functional Graphical Models for Manufacturing Process Modeling,” IEEE Transactions on Automation Science and Engineering, 14, 1612–1621. DOI: https://doi.org/10.1109/TASE.2017.2693398.
- Taylor, J. E., Worsley, K. J., and Gosselin, F. (2007), “Model Selection and Estimation in the Gaussian Graphical Model,” Biometrika, 94, 19–35. DOI: https://doi.org/10.1093/biomet/asm018.
- Tibshirani, R. (1996), “Regression Shrinkage and Selection Via the Lasso,” Journal of the Royal Statistical Society, Series B, 58, 267–288. DOI: https://doi.org/10.1111/j.2517-6161.1996.tb02080.x.
- Wang, Y., Mei, Y., and Paynabar, K. (2018), “Thresholded Multivariate Principal Component Analysis for Phase I Multichannel Profile Monitoring,” Technometrics, 60, 360–372. DOI: https://doi.org/10.1080/00401706.2017.1375993.
- Yang, S., Lu, Z., Shen, X., Wonka, P., and Ye, J. (2015), “Fused Multiple Graphical Lasso,” SIAM Journal on Optimization, 25, 916–943. DOI: https://doi.org/10.1137/130936397.
- Zhang, C., Yan, H., Lee, S., and Shi, J. (2018), “Weakly Correlated Profile Monitoring Based on Sparse Multi-Channel Functional Principal Component Analysis,” IISE Transactions, 50, 878–891. DOI: https://doi.org/10.1080/24725854.2018.1451012.
- Zhu, H., Strawn, N., and Dunson, D. (2016), “Bayesian Graphical Models for Multivariate Functional Data,” Journal of Machine Learning Research, 17, 1–27.
- Zou, C., Ning, X., and Tsung, F. (2012), “Lasso-Based Multivariate Linear Profile Monitoring,” Annals of Operations Research, 192, 3–19. DOI: https://doi.org/10.1007/s10479-010-0797-8.