Main References¶

The reference papers for the main methods in the package are listed below.

• Bouveyron C, Côme E, Jacques J. The discriminative functional mixture model for the analysis of bike sharing systems[J]. Preprint HAL, 2014 (01024186).

• Bouveyron C, Bozzi L, Jacques J, et al. The functional latent block model for the co-clustering of electricity consumption curves[J]. Journal of the Royal Statistical Society Series C: Applied Statistics, 2018, 67(4): 897-915.

• Galvani M, Torti A, Menafoglio A, et al. FunCC: A new bi-clustering algorithm for functional data with misalignment[J]. Computational Statistics & Data Analysis, 2021, 160: 107219.

• Fang K, Chen Y, Ma S, et al. Biclustering analysis of functionals via penalized fusion[J]. Journal of multivariate analysis, 2022, 189: 104874.

• Floriello D, Vitelli V. Sparse clustering of functional data[J]. Journal of Multivariate Analysis, 2017, 154: 1-18.

• Centofanti F, Lepore A, Palumbo B. Sparse and smooth functional data clustering[J]. Statistical Papers, 2024, 65(2): 795-825.

• Chen Y, Zhang Q, Ma S. Local clustering for functional data[J]. Journal of Computational and Graphical Statistics, 2025: 1-16.

• Prelić A, Bleuler S, Zimmermann P, et al. A systematic comparison and evaluation of biclustering methods for gene expression data[J]. Bioinformatics, 2006, 22(9): 1122-1129.

• Lee M, Shen H, Huang J Z, et al. Biclustering via sparse singular value decomposition[J]. Biometrics, 2010, 66(4): 1087-1095.

• Chi E C, Allen G I, Baraniuk R G. Convex biclustering[J]. Biometrics, 2017, 73(1): 10-19.

Other References¶

Additionally, the other references cited in the paper include: