PyDTS: A Python Package for Discrete-Time Survival Analysis with Competing Risks and Optional Penalization
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2022
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| _version_ | 1866909909643165696 |
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| author | Meir, Tomer Gutman, Rom Gorfine, Malka |
| author_facet | Meir, Tomer Gutman, Rom Gorfine, Malka |
| contents | Time-to-event (survival) analysis models the time until a pre-specified event occurs. When time is measured in discrete units or rounded into intervals, standard continuous-time models can yield biased estimators. In addition, the event of interest may belong to one of several mutually exclusive types, referred to as competing risks, where the occurrence of one event prevents the occurrence or observation of the others. PyDTS is an open-source Python package for analyzing discrete-time survival data with competing-risks. It provides regularized estimation methods, model evaluation metrics, variable screening tools, and a simulation module to support research and development. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2204_05731 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | PyDTS: A Python Package for Discrete-Time Survival Analysis with Competing Risks and Optional Penalization Meir, Tomer Gutman, Rom Gorfine, Malka Machine Learning Time-to-event (survival) analysis models the time until a pre-specified event occurs. When time is measured in discrete units or rounded into intervals, standard continuous-time models can yield biased estimators. In addition, the event of interest may belong to one of several mutually exclusive types, referred to as competing risks, where the occurrence of one event prevents the occurrence or observation of the others. PyDTS is an open-source Python package for analyzing discrete-time survival data with competing-risks. It provides regularized estimation methods, model evaluation metrics, variable screening tools, and a simulation module to support research and development. |
| title | PyDTS: A Python Package for Discrete-Time Survival Analysis with Competing Risks and Optional Penalization |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2204.05731 |