.actor_ffbs_path

Given period-wise sufficient statistics (H<a href="/link/t?package=lame&version=1.3.4" data-mini-rdoc="lame::t">t</a> = sum_j X^2_ij / s2,
h<a href="/link/t?package=lame&version=1.3.4" data-mini-rdoc="lame::t">t</a> = sum_j X_ij R_ij / s2) and AR(1) hyperparameters, returns one
joint draw from the posterior N(m, P) where the prior is AR(1) and
the observation is the Gaussian likelihood implied by (H, h).

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

.actor_ffbs_path function

<dl><dt>H</dt>
<dd>length-T vector of period-wise observation precisions</dd>
<dt>h</dt>
<dd>length-T vector of period-wise observation cross-products</dd>
<dt>rho_actor</dt>
<dd>AR(1) coefficient</dd>
<dt>sigma_actor2</dt>
<dd>AR(1) innovation variance</dd></dl>

Arguments

Given period-wise sufficient statistics (H<a href='https://rdrr.io/r/base/t.html'>t</a> = sum_j X^2_ij / s2,
h<a href='https://rdrr.io/r/base/t.html'>t</a> = sum_j X_ij R_ij / s2) and AR(1) hyperparameters, returns one
joint draw from the posterior N(m, P) where the prior is AR(1) and
the observation is the Gaussian likelihood implied by (H, h).

Univariate Carter-Kohn FFBS for one actor's length-T slope path — .actor_ffbs_path

<dl>

<dt>H</dt>
<dd>length-T vector of period-wise observation precisions</dd>


<dt>h</dt>
<dd>length-T vector of period-wise observation cross-products</dd>


<dt>rho_actor</dt>
<dd>AR(1) coefficient</dd>


<dt>sigma_actor2</dt>
<dd>AR(1) innovation variance</dd>

</dl>

.actor_ffbs_path: Univariate Carter-Kohn FFBS for one actor's length-T slope path

Description

Usage

Value

Arguments