rtnorm_interval_logp

Draws <code>z ~ N(ez, 1)</code> truncated to <code>(lb, ub)</code> for each cell,
working entirely on the log-probability scale in the tail that
contains the truncation interval. This stays exact for arbitrarily
extreme <code>ez</code> / bounds (log-scale <code>pnorm</code>/<code>qnorm</code> are
accurate to <code>|ez|</code> of several hundred), so no probability clamp
is needed. Infinite bounds reduce to the
one-sided case automatically.

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

rtnorm_interval_logp function

<dl><dt>ez</dt>
<dd>vector of conditional means.</dd>
<dt>lb</dt>
<dd>lower bounds (recycled to <code>length(ez)</code>).</dd>
<dt>ub</dt>
<dd>upper bounds (recycled to <code>length(ez)</code>).</dd></dl>

Arguments

Cassy Dorff, Shahryar Minhas, Tosin Salau

Author

Exact truncated-normal draw on (lb, ub) via the log.p-scale inverse CDF — rtnorm_interval_logp

<dl>

<dt>ez</dt>
<dd>vector of conditional means.</dd>


<dt>lb</dt>
<dd>lower bounds (recycled to <code>length(ez)</code>).</dd>


<dt>ub</dt>
<dd>upper bounds (recycled to <code>length(ez)</code>).</dd>

</dl>

rtnorm_interval_logp: Exact truncated-normal draw on (lb, ub) via the log.p-scale inverse CDF

Description

Usage

Value

Arguments

Author