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rmweather  

Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data
View on CRAN: Click here


Download and install rmweather package within the R console
Install from CRAN:
install.packages("rmweather")

Install from Github:
library("remotes")
install_github("cran/rmweather")

Install by package version:
library("remotes")
install_version("rmweather", "0.2.6")



Attach the package and use:
library("rmweather")
Maintained by
Stuart K. Grange
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-05-08
Latest Update: 2022-11-08
Description:
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) and Grange and Carslaw (2019) . 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) .
How to cite:
Stuart K. Grange (2018). rmweather: Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data. R package version 0.2.6, https://cran.r-project.org/web/packages/rmweather. Accessed 18 Feb. 2025.
Previous versions and publish date:
0.1.1 (2018-05-08 11:39), 0.1.2 (2018-07-16 09:40), 0.1.3 (2018-11-12 11:00), 0.1.4 (2020-05-26 11:30), 0.1.5 (2020-06-08 01:00), 0.1.51 (2020-06-15 08:50), 0.2.4 (2022-11-08 10:40), 0.2.5 (2023-11-21 15:10)
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