computeLogLik

Implements Bayesian spatio-temporal factor analysis models for multivariate data observed across space and time. The package provides tools for model fitting via Markov chain Monte Carlo (MCMC), spatial and temporal interpolation, and visualization of latent factors and loadings to support inference and exploration of underlying spatio-temporal patterns. Designed for use in environmental, ecological, or public health applications, with support for posterior prediction and uncertainty quantification. Includes functions such as BSTFA() for model fitting and plot_factor() to visualize the latent processes. Functions are based on and extended from methods described in Berrett, et al. (2020) <doi:10.1002/env.2609>.

Candace Berrett

BSTFA

Bayesian Spatio-Temporal Factor Analysis Model

Adam Simpson

computeLogLik function

<dl><dt>out</dt>
<dd>Output from BSTFA or BSTFAfull.</dd>
<dt>verbose</dt>
<dd>Logical scalar indicating whether to print status of the log-likelihood computation. Default is <code>FALSE</code>.</dd>
<dt>addthin</dt>
<dd>Numeric scalar indicating the number of additional draws to thin by to reduce the computation time. Default is <code>1</code> (no additional thinning).</dd></dl>

Arguments

Author

Compute log-likelihood — computeLogLik

<dl>

<dt>out</dt>
<dd>Output from BSTFA or BSTFAfull.</dd>


<dt>verbose</dt>
<dd>Logical scalar indicating whether to print status of the log-likelihood computation. Default is <code>FALSE</code>.</dd>


<dt>addthin</dt>
<dd>Numeric scalar indicating the number of additional draws to thin by to reduce the computation time. Default is <code>1</code> (no additional thinning).</dd>

</dl>

computeLogLik: Compute log-likelihood

Description

Usage

Value

Arguments

Author

Examples