simY_frn

Simulate a sociomatrix of fixed rank nominations from a social relations
model. A latent matrix <code>Z</code> is drawn from the SRM, and each sender's
outgoing ties are converted into ranked nominations: at most <code>odmax</code>
partners are nominated, only positive latent affinities qualify, and the
retained nominations are numbered from weakest (1) to strongest.

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

simY_frn function

<dl><dt>EZ</dt>
<dd>a square matrix giving the expected value of the latent Z matrix</dd>
<dt>rho</dt>
<dd>dyadic correlation</dd>
<dt>odmax</dt>
<dd>a scalar or vector giving the maximum number of nominations for
each node</dd>
<dt>YO</dt>
<dd>a square matrix identifying where missing values should be
maintained</dd></dl>

Arguments

Author

Simulate a relational matrix under a fixed rank nomination scheme — simY_frn

<dl>

<dt>EZ</dt>
<dd>a square matrix giving the expected value of the latent Z matrix</dd>


<dt>rho</dt>
<dd>dyadic correlation</dd>


<dt>odmax</dt>
<dd>a scalar or vector giving the maximum number of nominations for
each node</dd>


<dt>YO</dt>
<dd>a square matrix identifying where missing values should be
maintained</dd>

</dl>

simY_frn: Simulate a relational matrix under a fixed rank nomination scheme

Description

Usage

Value

Arguments

Author