References
- Bahadori, M. T. , Kale, D. , Fan, Y. , and Liu, Y. (2015), “Functional Subspace Clustering With Application to Time Series,” in International Conference on Machine Learning , pp. 228–237.
- Berrendero, J. R. , Bueno-Larraz, B. , and Cuevas, A. (2020), “On Mahalanobis Distance in Functional Settings,” Journal of Machine Learning Research , 21, 1–33.
- Chiou, J.-M. , Chen, Y.-T. , and Yang, Y.-F. (2014), “Multivariate Functional Principal Component Analysis: A Normalization Approach,” Statistica Sinica , 24, 1571–1596. DOI: https://doi.org/10.5705/ss.2013.305.
- Chiou, J.-M. , and Müller, H.-G. (2014), “Linear Manifold Modelling of Multivariate Functional Data,” Journal of the Royal Statistical Society, Series B, 76, 605–626. DOI: https://doi.org/10.1111/rssb.12038.
- Chiou, J.-M. , and Müller, H.-G. (2016), “A Pairwise Interaction Model for Multivariate Functional and Longitudinal Data,” Biometrika , 103, 377. DOI: https://doi.org/10.1093/biomet/asw007.
- Di, C.-Z. , Crainiceanu, C. M. , Caffo, B. S. , and Punjabi, N. M. (2009), “Multilevel Functional Principal Component Analysis,” The Annals of Applied Statistics , 3, 458. DOI: https://doi.org/10.1214/08-AOAS206.
- Dubin, J. A. , and Müller, H.-G. (2005), “Dynamical Correlation for Multivariate Longitudinal Data,” Journal of the American Statistical Association , 100, 872–881. DOI: https://doi.org/10.1198/016214504000001989.
- Elhamifar, E. , and Vidal, R. (2013), “Sparse Subspace Clustering: Algorithm, Theory, and Applications,” IEEE Transactions on Pattern Analysis and Machine Intelligence , 35, 2765–2781. DOI: https://doi.org/10.1109/TPAMI.2013.57.
- Fieuws, S. , and Verbeke, G. (2006), “Pairwise Fitting of Mixed Models for the Joint Modeling of Multivariate Longitudinal Profiles,” Biometrics , 62, 424–431. DOI: https://doi.org/10.1111/j.1541-0420.2006.00507.x.
- Gabel, M. , Gilad-Bachrach, R. , Renshaw, E. , and Schuster, A. (2016), “Full Body Gait Analysis With Kinect,” in 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society , IEEE, pp. 1964–1967.
- Gohberg, I. , and Goldberg, S. (2013), Basic Operator Theory , Basel: Birkhäuser.
- Huang, J. Z. , Shen, H. , and Buja, A. (2008), “Functional Principal Components Analysis via Penalized Rank One Approximation,” Electronic Journal of Statistics , 2, 678–695. DOI: https://doi.org/10.1214/08-EJS218.
- Keogh, E. (2002), “Exact Indexing of Dynamic Time Warping,” in Proceedings of the 28th International Conference on Very Large Data Bases , VLDB Endowment, pp. 406–417.
- Kolar, M. , and Xing, E. P. (2011), “On Time Varying Undirected Graphs,” in Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics , pp. 407–415.
- Kolar, M. , and Xing, E. P. (2012), “Estimating Networks With Jumps,” Electronic Journal of Statistics , 6, 2069. DOI: https://doi.org/10.1214/12-EJS739.
- Leurgans, S. E. , Moyeed, R. A. , and Silverman, B. W. (1993), “Canonical Correlation Analysis When the Data Are Curves,” Journal of the Royal Statistical Society, Series B, 55, 725–740. DOI: https://doi.org/10.1111/j.2517-6161.1993.tb01936.x.
- 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.
- Liu, J. , Yuan, L. , and Ye, J. (2010), “An Efficient Algorithm for a Class of Fused Lasso Problems,” in Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, pp. 323–332. DOI: https://doi.org/10.1145/1835804.1835847.
- Meinshausen, N. , and Bühlmann, P. (2006), “High-Dimensional Graphs and Variable Selection With the Lasso,” The Annals of Statistics , 34, 1436–1462. DOI: https://doi.org/10.1214/009053606000000281.
- Nemirovski, A. (2005), “Efficient Methods in Convex Programming,” Lecture Notes, Georgia Institution of Technology, https://www2.isye.gatech.edu/∼nemirovs/LecEMCO.pdf
- Ng, A. Y. , Jordan, M. I. , and Weiss, Y. (2001), “On Spectral Clustering: Analysis and an Algorithm,” in NIPS (Vol. 14), pp. 849–856.
- Nowak, G. , Hastie, T. , Pollack, J. R. , and Tibshirani, R. (2011), “A Fused Lasso Latent Feature Model for Analyzing Multi-Sample aCGH Data,” Biostatistics , 12, 776–791. DOI: https://doi.org/10.1093/biostatistics/kxr012.
- Pan, J. , and Yao, Q. (2008), “Modelling Multiple Time Series via Common Factors,” Biometrika , 95, 365–379. DOI: https://doi.org/10.1093/biomet/asn009.
- 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.
- Qiao, X. , Guo, S. , and James, G. M. (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. , and James, G. M. (2020), “Doubly Functional Graphical Models in High Dimensions,” Biometrika , 107, 415–431. DOI: https://doi.org/10.1093/biomet/asz072.
- Tibshirani, R. , Saunders, M. , Rosset, S. , Zhu, J. , and Knight, K. (2005), “Sparsity and Smoothness via the Fused Lasso,” Journal of the Royal Statistical Society, Series B, 67, 91–108. DOI: https://doi.org/10.1111/j.1467-9868.2005.00490.x.
- Wang, Y.-X. , and Xu, H. (2016), “Noisy Sparse Subspace Clustering,” The Journal of Machine Learning Research , 17, 320–360.
- Xiang, D. , Qiu, P. , and Pu, X. (2013), “Nonparametric Regression Analysis of Multivariate Longitudinal Data,” Statistica Sinica , 23, 769–789. DOI: https://doi.org/10.5705/ss.2011.317.
- Yang, W. , Müller, H.-G. , and Stadtmüller, U. (2011), “Functional Singular Component Analysis,” Journal of the Royal Statistical Society, Series B, 73, 303–324. DOI: https://doi.org/10.1111/j.1467-9868.2010.00769.x.
- Yuan, M. , and Lin, Y. (2007), “Model Selection and Estimation in the Gaussian Graphical Model,” Biometrika , 94, 19–35. DOI: https://doi.org/10.1093/biomet/asm018.
- Zhang, C. , Yan, H. , Lee, S. , and Shi, J. (2018a), “Multiple Profiles Sensor-Based Monitoring and Anomaly Detection,” Journal of Quality Technology , 50, 344–362. DOI: https://doi.org/10.1080/00224065.2018.1508275.
- Zhang, C. , Yan, H. , Lee, S. , and Shi, J. (2018b), “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.
- Zhou, S. , Lafferty, J. , and Wasserman, L. (2010), “Time Varying Undirected Graphs,” Machine Learning , 80, 295–319. DOI: https://doi.org/10.1007/s10994-010-5180-0.
- Zhu, H. , Strawn, N. , and Dunson, D. B. (2016), “Bayesian Graphical Models for Multivariate Functional Data,” Journal of Machine Learning Research , 17, 1–27.