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rmweather: Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data
An integrated set of tools to allow data users to conduct meteorological normalisation and counterfactual modelling for air quality data. The meteorological normalisation technique uses predictive random forest models to remove variation of pollutant concentrations so trends and interventions can be explored in a robust way. For examples, see Grange et al. (2018) <doi:10.5194/acp-18-6223-2018> and Grange and Carslaw (2019) <doi:10.1016/j.scitotenv.2018.10.344>. The random forest models can also be used for counterfactual or business as usual (BAU) modelling by using the models to predict, from the model's perspective, the future. For an example, see Grange et al. (2021) <doi:10.5194/acp-2020-1171>.
Getting started
Browse package contents
Package details |
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| Author | Stuart K. Grange [cre, aut] (<https://orcid.org/0000-0003-4093-3596>) |
| Maintainer | Stuart K. Grange <stuart.grange@york.ac.uk> |
| License | GPL-3 | file LICENSE |
| Version | 0.2.6 |
| URL | https://github.com/skgrange/rmweather |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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