rZ_ord_sym_fc

Symmetric-Z analogue of <code>rZ_ord_fc</code>: each unordered actor pair
carries one latent value (<code>Z[i, j] = Z[j, i]</code>) drawn from a
truncated normal with mean equal to the average linear predictor
(EZ_ij + EZ_ji) / 2 and variance 1 (the model's conditional). The
lower triangle is mirrored after the upper-triangle draws so the full
matrix is exactly symmetric at every sweep.

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_ord_sym_fc function

<dl><dt>Z</dt>
<dd>current symmetric latent matrix (n x n, Z = t(Z)).</dd>
<dt>EZ</dt>
<dd>expected value of Z (regression + additive + multiplicative
contributions); can be asymmetric, the helper averages the two
directed contributions.</dd>
<dt>Y</dt>
<dd>observed symmetric ordinal matrix (n x n, Y = t(Y));
diagonal is ignored.</dd></dl>

Arguments

Cassy Dorff, Shahryar Minhas, Tosin Salau

Author

Sample Z under symmetric ordinal data (square symmetric matrix) — rZ_ord_sym_fc

<dl>

<dt>Z</dt>
<dd>current symmetric latent matrix (n x n, Z = t(Z)).</dd>


<dt>EZ</dt>
<dd>expected value of Z (regression + additive + multiplicative
contributions); can be asymmetric, the helper averages the two
directed contributions.</dd>


<dt>Y</dt>
<dd>observed symmetric ordinal matrix (n x n, Y = t(Y));
diagonal is ignored.</dd>

</dl>

rZ_ord_sym_fc: Sample Z under symmetric ordinal data (square symmetric matrix)

Description

Usage

Value

Arguments

Author