sampler_describe

sampler_describe.ame_als

sampler_describe.boot_ame

sampler_describe.ame

sampler_describe.lame

Reports which estimation routine produced a fitted object and what
uncertainty information, if any, is available. Methods exist for
<code>ame_als</code> fits (the fast block coordinate descent estimator) and
<code>boot_ame</code> bootstrap objects.

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

sampler_describe function

<dl><dt>object</dt>
<dd>a fitted object (<code>ame_als</code> or <code>boot_ame</code>).</dd>
<dt>verbose</dt>
<dd>logical; if <code>TRUE</code> (default) print the description.</dd></dl>

Arguments

Describe the estimator behind a fitted object — sampler_describe

<dl>

<dt>object</dt>
<dd>a fitted object (<code>ame_als</code> or <code>boot_ame</code>).</dd>


<dt>verbose</dt>
<dd>logical; if <code>TRUE</code> (default) print the description.</dd>

</dl>

sampler_describe: Describe the estimator behind a fitted object

Description

Usage

Value

Arguments