rs2_rep_fc

Gibbs update for dyadic variance with independent replicate relational 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

rs2_rep_fc function

<dl><dt>E.T</dt>
<dd>Array of square residual relational matrix series. The third
dimension of the array is for different replicates. Each slice of the array
according to the third dimension is a square residual relational matrix</dd>
<dt>rho</dt>
<dd>current value of rho</dd></dl>

Arguments

Author

Gibbs update for dyadic variance with independent replicate relational data — rs2_rep_fc

<dl>

<dt>E.T</dt>
<dd>Array of square residual relational matrix series. The third
dimension of the array is for different replicates. Each slice of the array
according to the third dimension is a square residual relational matrix</dd>


<dt>rho</dt>
<dd>current value of rho</dd>

</dl>

rs2_rep_fc: Gibbs update for dyadic variance with independent replicate relational data

Description

Usage

Value

Arguments

Author