mgwrsar_bootstrap_test

A bootstrap test for Betas for mgwrsar class model.

Functions for computing (Mixed and Multiscale) Geographically Weighted Regression with spatial autocorrelation, Geniaux and Martinetti (2017) <doi:10.1016/j.regsciurbeco.2017.04.001>.

Ghislain Geniaux

mgwrsar

GWR, Mixed GWR and Multiscale GWR with Spatial Autocorrelation

Davide Martinetti

César Martinez

mgwrsar_bootstrap_test function

<dl><dt>x0</dt>
<dd>The H0 mgwrsar model</dd>
<dt>x1</dt>
<dd>The H1 mgwrsar model</dd>
<dt>B</dt>
<dd>number of bootstrap repetitions, default 100</dd>
<dt>doMC</dt>
<dd>If TRUE, doParallel parallelization</dd>
<dt>ncore</dt>
<dd>number of cores</dd>
<dt>type</dt>
<dd>type of bootstap : 'wild','Rademacher','spatial' or 'standard' (default)</dd>
<dt>eps</dt>
<dd>Hypothesis under wich residuals are simulated, 'H0' or 'H1' (default)</dd>
<dt>df</dt>
<dd>Hypothesis under wich degree of freedom is estimated.</dd>
<dt>focal</dt>
<dd>see sample_stat help</dd>
<dt>D</dt>
<dd>A matrix of distance</dd></dl>

Arguments

A bootstrap test for Betas for mgwrsar class model. — mgwrsar_bootstrap_test

<dl>

<dt>x0</dt>
<dd>The H0 mgwrsar model</dd>


<dt>x1</dt>
<dd>The H1 mgwrsar model</dd>


<dt>B</dt>
<dd>number of bootstrap repetitions, default 100</dd>


<dt>doMC</dt>
<dd>If TRUE, doParallel parallelization</dd>


<dt>ncore</dt>
<dd>number of cores</dd>


<dt>type</dt>
<dd>type of bootstap : 'wild','Rademacher','spatial' or 'standard' (default)</dd>


<dt>eps</dt>
<dd>Hypothesis under wich residuals are simulated, 'H0' or 'H1' (default)</dd>


<dt>df</dt>
<dd>Hypothesis under wich degree of freedom is estimated.</dd>


<dt>focal</dt>
<dd>see sample_stat help</dd>


<dt>D</dt>
<dd>A matrix of distance</dd>

</dl>

mgwrsar_bootstrap_test: A bootstrap test for Betas for mgwrsar class model.

Description

Usage

Value

Arguments

See Also