rZ_rrl_fc

Simulates a random latent matrix Z given its expectation, dyadic correlation
and relative rank nomination data

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_rrl_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 matrix of ranked nomination data</dd>
<dt>YL</dt>
<dd>list of ranked individuals, from least to most preferred in each
row</dd></dl>

Arguments

Author

Simulate Z given relative rank nomination data — rZ_rrl_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 matrix of ranked nomination data</dd>


<dt>YL</dt>
<dd>list of ranked individuals, from least to most preferred in each
row</dd>

</dl>

rZ_rrl_fc: Simulate Z given relative rank nomination data

Description

Usage

Value

Arguments

Author

Details