Cluster weighted models with multivariate skewed distributions for functional data
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866913797299503104 |
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| author | Anton, Cristina Shreshtth, Roy Shivam Ram |
| author_facet | Anton, Cristina Shreshtth, Roy Shivam Ram |
| contents | We propose a clustering method, funWeightClustSkew, based on mixtures of functional linear regression models and three skewed multivariate distributions: the variance-gamma distribution, the skew-t distribution, and the normal-inverse Gaussian distribution. Our approach follows the framework of the functional high dimensional data clustering (funHDDC) method, and we extend to functional data the cluster weighted models based on skewed distributions used for finite dimensional multivariate data. We consider several parsimonious models, and to estimate the parameters we construct an expectation maximization (EM) algorithm. We illustrate the performance of funWeightClustSkew for simulated data and for the Air Quality dataset. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_12683 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cluster weighted models with multivariate skewed distributions for functional data Anton, Cristina Shreshtth, Roy Shivam Ram Methodology Machine Learning We propose a clustering method, funWeightClustSkew, based on mixtures of functional linear regression models and three skewed multivariate distributions: the variance-gamma distribution, the skew-t distribution, and the normal-inverse Gaussian distribution. Our approach follows the framework of the functional high dimensional data clustering (funHDDC) method, and we extend to functional data the cluster weighted models based on skewed distributions used for finite dimensional multivariate data. We consider several parsimonious models, and to estimate the parameters we construct an expectation maximization (EM) algorithm. We illustrate the performance of funWeightClustSkew for simulated data and for the Air Quality dataset. |
| title | Cluster weighted models with multivariate skewed distributions for functional data |
| topic | Methodology Machine Learning |
| url | https://arxiv.org/abs/2504.12683 |