Modelling phenology using ordered categorical generalized additive models
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866915439561408512 |
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| author | Miller, David L |
| author_facet | Miller, David L |
| contents | One form of data collected in ecology is phenological, describing the timing of life stages. It can be tempting to analyze such data using a continuous distribution or to model individual transitions via probit/logit models. Such simplifications can lead to incorrect inference in various ways, all of which stem from ignoring the natural structure of the data. This paper presents a flexible approach to modelling ordered categorical data using the popular R package `mgcv`. An example analysis of saxifrage phenology in Greenland including useful plots, model checking and derived quantities is included. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_07789 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Modelling phenology using ordered categorical generalized additive models Miller, David L Methodology Quantitative Methods One form of data collected in ecology is phenological, describing the timing of life stages. It can be tempting to analyze such data using a continuous distribution or to model individual transitions via probit/logit models. Such simplifications can lead to incorrect inference in various ways, all of which stem from ignoring the natural structure of the data. This paper presents a flexible approach to modelling ordered categorical data using the popular R package `mgcv`. An example analysis of saxifrage phenology in Greenland including useful plots, model checking and derived quantities is included. |
| title | Modelling phenology using ordered categorical generalized additive models |
| topic | Methodology Quantitative Methods |
| url | https://arxiv.org/abs/2508.07789 |