Probabilistic curve-aligned clustering and prediction with regression mixture models
Probabilistic curve-aligned clustering and prediction with regression mixture models
Decision tree state tying based on penalized Bayesian information criterion
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
k-mean alignment for curve clustering
Computational Statistics & Data Analysis
Identifying cluster number for subspace projected functional data clustering
Computational Statistics & Data Analysis
Phase and amplitude-based clustering for functional data
Computational Statistics & Data Analysis
Model-based clustering for multivariate functional data
Computational Statistics & Data Analysis
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Study of dynamic processes in many areas of science has led to the appearance of functional data sets. It is often the case that individual trajectories vary both in the amplitude space and in the time space. We develop a coherent clustering procedure that allows for temporal aligning. Under this framework, closed form solutions of an EM type learning algorithm are derived. The method can be applied to all types of curve data but is particularly useful when phase variation is present. We demonstrate the method by both simulation studies and an application to human growth curves.