FDApy: a Python package for functional data
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arXiv
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| Format: | Preprint |
| Published: |
2021
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| _version_ | 1866912262916145152 |
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| author | Golovkine, Steven |
| author_facet | Golovkine, Steven |
| contents | We introduce FDApy, an open-source Python package for the analysis of functional data. The package provides tools for the representation of (multivariate) functional data defined on different dimensional domains and for functional data that is irregularly sampled. Additionally, dimension reduction techniques are implemented for multivariate and/or multidimensional functional data that are regularly or irregularly sampled. A toolbox for generating functional datasets is also provided. The documentation includes installation and usage instructions, examples on simulated and real datasets and a complete description of the API. FDApy is released under the MIT license. The code and documentation are available at https://github.com/StevenGolovkine/FDApy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2101_11003 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | FDApy: a Python package for functional data Golovkine, Steven Mathematical Software Machine Learning Computation 62R10 (Primary) We introduce FDApy, an open-source Python package for the analysis of functional data. The package provides tools for the representation of (multivariate) functional data defined on different dimensional domains and for functional data that is irregularly sampled. Additionally, dimension reduction techniques are implemented for multivariate and/or multidimensional functional data that are regularly or irregularly sampled. A toolbox for generating functional datasets is also provided. The documentation includes installation and usage instructions, examples on simulated and real datasets and a complete description of the API. FDApy is released under the MIT license. The code and documentation are available at https://github.com/StevenGolovkine/FDApy. |
| title | FDApy: a Python package for functional data |
| topic | Mathematical Software Machine Learning Computation 62R10 (Primary) |
| url | https://arxiv.org/abs/2101.11003 |