rZ_bin_fc

Simulates a random latent matrix Z given its expectation, dyadic correlation
and a binary relational matrix Y

Analysis of dyadic network and relational data using additive and
multiplicative effects (AME) models. The basic model includes
regression terms, the covariance structure of the social relations model
(Warner, Kenny and Stoto (1979) <DOI:10.1037/0022-3514.37.10.1742>,
Wong (1982) <DOI:10.2307/2287296>), and multiplicative factor
models (Hoff(2009) <DOI:10.1007/s10588-008-9040-4>).
Several different link functions accommodate different
relational data structures, including binary/network data, normal
relational data, zero-inflated positive outcomes using a tobit model, ordinal relational data and data from
fixed-rank nomination schemes. Several of these link functions are
discussed in Hoff, Fosdick, Volfovsky and Stovel (2013)
<DOI:10.1017/nws.2013.17>. Development of this
software was supported in part by NIH grant R01HD067509.

Peter Hoff

amen

Additive and Multiplicative Effects Models for Networks and
Relational Data

Bailey Fosdick

Alex Volfovsky

Yanjun He

rZ_bin_fc function

<dl><dt>Z</dt>
<dd>a square matrix, the current value of Z</dd>
<dt>EZ</dt>
<dd>expected value of Z</dd>
<dt>rho</dt>
<dd>dyadic correlation</dd>
<dt>Y</dt>
<dd>square binary relational matrix</dd></dl>

Arguments

Author

Simulate Z based on a probit model — rZ_bin_fc

<dl>

<dt>Z</dt>
<dd>a square matrix, the current value of Z</dd>


<dt>EZ</dt>
<dd>expected value of Z</dd>


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


<dt>Y</dt>
<dd>square binary relational matrix</dd>

</dl>

rZ_bin_fc: Simulate Z based on a probit model

Description

Usage

Value

Arguments

Author