rmfnchypg

Random generation for multivariate non-central hypergeometric

Implements atom-based regression models (ABRM) for analyzing spatially
misaligned data. Provides functions for simulating misaligned spatial data,
preparing NIMBLE model inputs, running MCMC diagnostics, and comparing different
spatial analysis methods including dasymetric mapping. All main functions return
S3 objects with print(), summary(), and plot() methods for intuitive result exploration.
Methods are described in Nethery et al. (2023) <doi:10.1101/2023.01.10.23284410>.
Further methodological details and software implementation are described in Qian et al. (in review).

Yunzhe Qian

spatialAtomizeR

Spatial Analysis with Misaligned Data Using Atom-Based
Regression Models

Rachel Nethery

Nancy Krieger

Nykesha Johnson

rmfnchypg function

<dl><dt>n</dt>
<dd>number of observations (only n=1 is used)</dd>
<dt>total</dt>
<dd>Total number of items</dd>
<dt>odds</dt>
<dd>Vector of odds</dd>
<dt>ni</dt>
<dd>Vector of category sizes</dd></dl>

Arguments

Random generation for multivariate non-central hypergeometric — rmfnchypg

<dl>

<dt>n</dt>
<dd>number of observations (only n=1 is used)</dd>


<dt>total</dt>
<dd>Total number of items</dd>


<dt>odds</dt>
<dd>Vector of odds</dd>


<dt>ni</dt>
<dd>Vector of category sizes</dd>

</dl>

rmfnchypg: Random generation for multivariate non-central hypergeometric

Description

Usage

Value

Arguments