expected_mc

Expected value for the Moran coefficient of model residuals under the null hypothesis of no spatial autocorrelation.

For spatial data analysis; provides exploratory spatial analysis tools, spatial regression, spatial econometric, and disease mapping models, model diagnostics, and special methods for inference with small area survey data (e.g., the America Community Survey (ACS)) and censored population health monitoring data. Models are pre-specified using the Stan programming language, a platform for Bayesian inference using Markov chain Monte Carlo (MCMC). References: Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>; Donegan (2021) <doi:10.31219/osf.io/3ey65>; Donegan (2022) <doi:10.21105/joss.04716>; Donegan, Chun and Hughes (2020) <doi:10.1016/j.spasta.2020.100450>; Donegan, Chun and Griffith (2021) <doi:10.3390/ijerph18136856>; Morris et al. (2019) <doi:10.1016/j.sste.2019.100301>.

Connor Donegan

geostan

Bayesian Spatial Analysis

Mitzi Morris

Amy Tims

expected_mc function

<dl><dt>X</dt>
<dd>model matrix, including column of ones.</dd>
<dt>C</dt>
<dd>Connectivity matrix.</dd></dl>

Arguments

Expected value of the residual Moran coefficient — expected_mc

<dl>

<dt>X</dt>
<dd>model matrix, including column of ones.</dd>


<dt>C</dt>
<dd>Connectivity matrix.</dd>

</dl>

expected_mc: Expected value of the residual Moran coefficient

Description

Usage

Value

Arguments

Examples