is.spBFA

<code>is.spBFA</code> is a general test of an object being interpretable as a
<code>spBFA</code> object.

Implements a spatial Bayesian non-parametric factor analysis model
with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC).
Spatial correlation is introduced in the columns of the factor loadings
matrix using a Bayesian non-parametric prior, the probit stick-breaking
process. Areal spatial data is modeled using a conditional autoregressive
(CAR) prior and point-referenced spatial data is treated using a Gaussian
process. The response variable can be modeled as Gaussian, probit, Tobit, or
Binomial (using Polya-Gamma augmentation). Temporal correlation is
introduced for the latent factors through a hierarchical structure and can
be specified as exponential or first-order autoregressive. Full details of
the package can be found in the accompanying vignette. Furthermore, the
details of the package can be found in "Bayesian Non-Parametric Factor
Analysis for Longitudinal Spatial Surfaces", by Berchuck et al (2019),
<doi:10.1214/20-BA1253> in Bayesian Analysis.

Samuel I. Berchuck

spBFA

Spatial Bayesian Factor Analysis

is.spBFA function

<dl><dt>x</dt>
<dd>object to be tested.</dd></dl>

Arguments

is.spBFA — is.spBFA

<dl>

<dt>x</dt>
<dd>object to be tested.</dd>

</dl>

is.spBFA: is.spBFA

Description

Usage

Value

Arguments

Details

Examples