rmvnorm

Simulates a matrix where the rows are i.i.d. samples from a multivariate
normal distribution

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

rmvnorm function

<dl><dt>n</dt>
<dd>sample size</dd>
<dt>mu</dt>
<dd>multivariate mean vector</dd>
<dt>Sigma</dt>
<dd>covariance matrix</dd>
<dt>Sigma.chol</dt>
<dd>Cholesky factorization of <code>Sigma</code></dd></dl>

Arguments

Author

Simulation from a multivariate normal distribution — rmvnorm

<dl>

<dt>n</dt>
<dd>sample size</dd>


<dt>mu</dt>
<dd>multivariate mean vector</dd>


<dt>Sigma</dt>
<dd>covariance matrix</dd>


<dt>Sigma.chol</dt>
<dd>Cholesky factorization of <code>Sigma</code></dd>

</dl>

rmvnorm: Simulation from a multivariate normal distribution

Description

Usage

Value

Arguments

Author