YX_bin_list

The list-form sibling of <code>YX_bin_long</code>: same synthetic
4-period 50-actor panel reshaped from arrays to lists. The shipped
<code>Y</code> entries hold the latent probit-scale predictor
(range roughly -20 to 17), not 0/1 ties. To recover the binary tie
indicator the dataset name implies, threshold at zero, e.g.
<code>Y_bin &lt;- lapply(YX_bin_list$Y, function(Yt) 1 * (Yt &gt; 0))</code>.
If passed unthresholded to <code>lame(..., family = "binary")</code> the
fit will warn and silently apply the same <code>Y &gt; 0</code> threshold.

datasets

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

YX_bin_list function

A list with two elements:<dl>
<dt>Y</dt>
<dd>List of 4 numeric matrices, each <code>[50, 50]</code>, with
<code>NA</code> on the diagonal. Latent probit-scale predictor;
threshold at 0 for the binary indicator.</dd><dt>X</dt>
<dd>List of 4 numeric arrays, each <code>[50, 50, 3]</code> of
dyadic covariates.</dd>
</dl>

Format

Synthetic longitudinal binary relational data, list-form (latent-scale) — YX_bin_list

A list with two elements:<dl>
<dt>Y</dt>
<dd>List of 4 numeric matrices, each <code>[50, 50]</code>, with
<code>NA</code> on the diagonal. Latent probit-scale predictor;
threshold at 0 for the binary indicator.</dd>

<dt>X</dt>
<dd>List of 4 numeric arrays, each <code>[50, 50, 3]</code> of
dyadic covariates.</dd>


</dl>

YX_bin_list: Synthetic longitudinal binary relational data, list-form (latent-scale)

Description

Arguments

Format