aple

The approximate-profile likelihood estimator for the spatial autocorrelation parameter from a simultaneous autoregressive (SAR) model (Li et al. 2007).

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

aple function

<dl><dt>x</dt>
<dd>Numeric vector of values, length <code>n</code>. This will be standardized internally with <code>scale(x)</code>.</dd>
<dt>w</dt>
<dd>An <code>n x n</code> row-standardized spatial connectivity matrix. See shape2mat.</dd>
<dt>digits</dt>
<dd>Number of digits to round results to.</dd></dl>

Arguments

Spatial autocorrelation estimator — aple

<dl>

<dt>x</dt>
<dd>Numeric vector of values, length <code>n</code>. This will be standardized internally with <code>scale(x)</code>.</dd>


<dt>w</dt>
<dd>An <code>n x n</code> row-standardized spatial connectivity matrix. See shape2mat.</dd>


<dt>digits</dt>
<dd>Number of digits to round results to.</dd>

</dl>

aple: Spatial autocorrelation estimator

Description

Usage

Value

Arguments

Details

See Also

Examples