get_distexp

`get_distexp()` takes counterfactual densities and
and returns the expected number of treatment events based on distances
from a user-specified focus.

Spatio-temporal causal inference based on point process data.
You provide the raw data of locations and timings of treatment and
outcome events, specify counterfactual scenarios, and the package
estimates causal effects over specified spatial and temporal windows.
See Papadogeorgou, et al. (2022) <doi:10.1111/rssb.12548> and
Mukaigawara, et al. (2024) <doi:10.31219/osf.io/5kc6f>.

Mitsuru Mukaigawara

geocausal

Causal Inference with Spatio-Temporal Data

Lingxiao Zhou

Georgia Papadogeorgou

Jason Lyall

Kosuke Imai

get_distexp function

<dl><dt>cf_sim_results</dt>
<dd>output of `sim_cf_dens()`</dd>
<dt>entire_window</dt>
<dd>owin object of the entire region</dd>
<dt>dist_map</dt>
<dd>im object whose cell values are the distance from a focus (e.g., city)</dd>
<dt>dist_map_unit</dt>
<dd>either `"km"` or `"mile"`</dd>
<dt>use_raw</dt>
<dd>logical. `use_raw` specifies whether to use the raw value of expectations or percentiles.
By default, `FALSE`.</dd></dl>

Arguments

Get the expectation of treatment events with arbitrary distances — get_distexp

<dl>

<dt>cf_sim_results</dt>
<dd>output of `sim_cf_dens()`</dd>


<dt>entire_window</dt>
<dd>owin object of the entire region</dd>


<dt>dist_map</dt>
<dd>im object whose cell values are the distance from a focus (e.g., city)</dd>


<dt>dist_map_unit</dt>
<dd>either `"km"` or `"mile"`</dd>


<dt>use_raw</dt>
<dd>logical. `use_raw` specifies whether to use the raw value of expectations or percentiles.
By default, `FALSE`.</dd>

</dl>

get_distexp: Get the expectation of treatment events with arbitrary distances

Description

Usage

Value

Arguments