rZ_pois_bip_fc

Rectangular analogue of <code>rZ_pois_fc</code>. Each <code>(i,j)</code>
cell is updated independently with a Metropolis-Hastings step on
the Poisson log-link; there is no upper/lower-triangle coupling and
no diagonal because the bipartite Y is <code>nA x nB</code> with disjoint
row and column actor sets.

internal

Additive and multiplicative effects models for both cross-sectional and longitudinal network analysis. The package provides two main functions: ame() for cross-sectional networks and lame() for longitudinal networks. It supports square and rectangular network structures. Key features include: (1) Cross-sectional network analysis via ame() with support for binary, continuous, ordinal, and count data; (2) Longitudinal network analysis via lame() with additive sender/receiver and multiplicative latent-factor effects that can evolve over time through AR(1) processes (Sewell and Chen (2015) <doi:10.1080/01621459.2014.988214>; Durante and Dunson (2014) <doi:10.1093/biomet/asu040>); (3) Handling of changing actor compositions across time periods in longitudinal models; (4) Performance improvements through C++ implementations via 'Rcpp' and 'RcppArmadillo'.

Shahryar Minhas

lame

Longitudinal Additive and Multiplicative Effects Models for
Networks

Cassy Dorff

Tosin Salau

rZ_pois_bip_fc function

<dl><dt>Z</dt>
<dd>current rectangular latent matrix (nA x nB).</dd>
<dt>EZ</dt>
<dd>expected value (regression + additive + multiplicative
effects), nA x nB.</dd>
<dt>s2</dt>
<dd>dyadic variance (proposal scale on the latent log-mean).</dd>
<dt>Y</dt>
<dd>observed count matrix (nA x nB); <code>NA</code> entries are
resampled from the prior.</dd>
<dt>log_exposure</dt>
<dd>optional per-period log-exposure offset (scalar
or matrix conformable with Y). Default <code>0</code>.</dd></dl>

Arguments

Cassy Dorff, Shahryar Minhas, Tosin Salau

Author

Sample Z under bipartite Poisson (rectangular MH step) — rZ_pois_bip_fc

<dl>

<dt>Z</dt>
<dd>current rectangular latent matrix (nA x nB).</dd>


<dt>EZ</dt>
<dd>expected value (regression + additive + multiplicative
effects), nA x nB.</dd>


<dt>s2</dt>
<dd>dyadic variance (proposal scale on the latent log-mean).</dd>


<dt>Y</dt>
<dd>observed count matrix (nA x nB); <code>NA</code> entries are
resampled from the prior.</dd>


<dt>log_exposure</dt>
<dd>optional per-period log-exposure offset (scalar
or matrix conformable with Y). Default <code>0</code>.</dd>

</dl>

rZ_pois_bip_fc: Sample Z under bipartite Poisson (rectangular MH step)

Description

Usage

Value

Arguments

Author