homophili.data

<code>homophili.data</code> converts the matrix of explanatory variables between directed network models and symmetric network models.

Simulating and estimating peer effect models and network formation models. The class of peer effect models includes linear-in-means models (Lee, 2004; <doi:10.1111/j.1468-0262.2004.00558.x>), Tobit models (Xu and Lee, 2015; <doi:10.1016/j.jeconom.2015.05.004>), and discrete numerical data models (Houndetoungan, 2024; <doi:10.2139/ssrn.3721250>). The network formation models include pair-wise regressions with degree heterogeneity (Graham, 2017; <doi:10.3982/ECTA12679>) and exponential random graph models (Mele, 2017; <doi:10.3982/ECTA10400>).

Aristide Houndetoungan

CDatanet

Econometrics of Network Data

homophili.data function

<dl><dt>data</dt>
<dd>A <code>matrix</code> or <code>data.frame</code> of the explanatory variables of the network formation model. This
corresponds to the <code>X</code> matrix in <code>homophily.fe</code> or <code>homophily.re</code>.</dd>
<dt>nvec</dt>
<dd>A vector of the number of individuals in the networks.</dd>
<dt>to</dt>
<dd>Indicates the direction of the conversion. For a matrix of explanatory variables <code>X</code> (<code>n*(n-1)</code> rows), one can
select lower triangular entries (<code>to = "lower"</code>) or upper triangular entries (<code>to = "upper"</code>).
For a triangular <code>X</code> (<code>n*(n-1)/2</code> rows), one can convert to a full matrix of <code>n*(n-1)</code> rows by using symmetry (<code>to = "symmetric"</code>).</dd></dl>

Arguments

Converting Data between Directed Network Models and Symmetric Network Models. — homophili.data

<dl>

<dt>data</dt>
<dd>A <code>matrix</code> or <code>data.frame</code> of the explanatory variables of the network formation model. This
corresponds to the <code>X</code> matrix in <code>homophily.fe</code> or <code>homophily.re</code>.</dd>


<dt>nvec</dt>
<dd>A vector of the number of individuals in the networks.</dd>


<dt>to</dt>
<dd>Indicates the direction of the conversion. For a matrix of explanatory variables <code>X</code> (<code>n*(n-1)</code> rows), one can
select lower triangular entries (<code>to = "lower"</code>) or upper triangular entries (<code>to = "upper"</code>).
For a triangular <code>X</code> (<code>n*(n-1)/2</code> rows), one can convert to a full matrix of <code>n*(n-1)</code> rows by using symmetry (<code>to = "symmetric"</code>).</dd>

</dl>

homophili.data: Converting Data between Directed Network Models and Symmetric Network Models.

Description

Usage

Value

Arguments