n_nbs

Count neighbors in a connectivity matrix

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

n_nbs function

<dl><dt>C</dt>
<dd>A connectivity matrix</dd></dl>

Arguments

Count neighbors in a connectivity matrix — n_nbs

<dl>

<dt>C</dt>
<dd>A connectivity matrix</dd>

</dl>

n_nbs: Count neighbors in a connectivity matrix

Description

Usage

Value

Arguments

Examples