rmw_find_breakpoints

<code>rmw_find_breakpoints</code> will generally be applied to a data frame after
<code>rmw_normalise</code>. <code>rmw_find_breakpoints</code> is rather slow.

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>.

Stuart K. Grange

rmweather

Tools to Conduct Meteorological Normalisation and Counterfactual
Modelling for Air Quality Data

rmw_find_breakpoints function

<dl><dt>df</dt>
<dd>Tibble from <code>rmw_normalise</code> to detect breakpoints 
in.</dd>
<dt>h</dt>
<dd>Minimal segment size either given as fraction relative to the sample 
size or as an integer giving the minimal number of observations in each 
segment.</dd>
<dt>n</dt>
<dd>Number of breaks to detect. Default is maximum number allowed by
<code>h</code>.</dd></dl>

Arguments

Author

Function to detect breakpoints in a data frame using a linear regression 
based approach. — rmw_find_breakpoints

<dl>

<dt>df</dt>
<dd>Tibble from <code>rmw_normalise</code> to detect breakpoints 
in.</dd>


<dt>h</dt>
<dd>Minimal segment size either given as fraction relative to the sample 
size or as an integer giving the minimal number of observations in each 
segment.</dd>


<dt>n</dt>
<dd>Number of breaks to detect. Default is maximum number allowed by
<code>h</code>.</dd>

</dl>

rmw_find_breakpoints: Function to detect breakpoints in a data frame using a linear regression based approach.

Description

Usage

Value

Arguments

Author

Examples