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) 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) .


Reference manual

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install.packages("rmweather")

0.2.63 by Stuart K. Grange, a year ago


https://github.com/skgrange/rmweather


Report a bug at https://github.com/skgrange/rmweather/issues


Browse source code at https://github.com/cran/rmweather


Authors: Stuart K. Grange [cre, aut] (ORCID:


Documentation:   PDF Manual  


GPL-3 | file LICENSE license


Imports dplyr, ggplot2, lubridate, magrittr, pdp, purrr, ranger, stringr, strucchange, tibble, viridis, tidyr, cli

Suggests testthat, openair


See at CRAN