.xbeta_newdata

Convenience wrapper: builds the full canonical design via
<code>.build_full_design</code> and contracts it against a named
coefficient vector. Because the design is rebuilt in the model's slice
order, the positional contraction is correct even with nodal covariates.

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

.xbeta_newdata function

<dl><dt>beta</dt>
<dd>named numeric coefficient vector (a single draw or the
posterior mean).</dd>
<dt>newdata</dt>
<dd>dyadic covariate array (see <code>.build_full_design</code>).</dd>
<dt>fitted_design</dt>
<dd>fitted design array (<code>fit$X</code>); held-fixed source
for intercept + nodal slices.</dd>
<dt>n, m</dt>
<dd>output dimensions.</dd></dl>

Arguments

Name-safe linear predictor from a newdata prediction — .xbeta_newdata

<dl>

<dt>beta</dt>
<dd>named numeric coefficient vector (a single draw or the
posterior mean).</dd>


<dt>newdata</dt>
<dd>dyadic covariate array (see <code>.build_full_design</code>).</dd>


<dt>fitted_design</dt>
<dd>fitted design array (<code>fit$X</code>); held-fixed source
for intercept + nodal slices.</dd>


<dt>n, m</dt>
<dd>output dimensions.</dd>

</dl>

.xbeta_newdata: Name-safe linear predictor from a newdata prediction

Description

Usage

Value

Arguments