sim_power_dens

A function that takes the target densities and their priorities
and returns a power density image over a range of parameters

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

sim_power_dens function

<dl><dt>target_dens</dt>
<dd>list of target densities. This should always be a list, even if there is only one target density.</dd>
<dt>dens_manip</dt>
<dd>a target density for which we manipulate the value of priorities</dd>
<dt>priorities</dt>
<dd>numeric. `priorities` specifies the priority for the target density that we do not manipulate.</dd>
<dt>priorities_manip</dt>
<dd>vector of priorities for the density that we manipulate.</dd>
<dt>window</dt>
<dd>owin object</dd></dl>

Arguments

Simulate power densities — sim_power_dens

<dl>

<dt>target_dens</dt>
<dd>list of target densities. This should always be a list, even if there is only one target density.</dd>


<dt>dens_manip</dt>
<dd>a target density for which we manipulate the value of priorities</dd>


<dt>priorities</dt>
<dd>numeric. `priorities` specifies the priority for the target density that we do not manipulate.</dd>


<dt>priorities_manip</dt>
<dd>vector of priorities for the density that we manipulate.</dd>


<dt>window</dt>
<dd>owin object</dd>

</dl>

sim_power_dens: Simulate power densities

Description

Usage

Value

Arguments