normalise_weights_to_counts

Divides the rank-<code>2K</code> array of weighted contact counts produced by
<code>weighted_matrix_array()</code> by the participant-side weight totals
(cross-tabulated over the same grouping columns), giving the mean
number of contacts per participant. Cells with no participants
become <code>NA</code>.

internal

Methods for sampling contact matrices from diary data for
use in infectious disease modelling, as discussed in Mossong et al.
(2008) <doi:10.1371/journal.pmed.0050074>.

Sebastian Funk

socialmixr

Social Mixing Matrices for Infectious Disease Modelling

Lander Willem

Hugo Gruson

Nicholas Tierney

Maria Bekker-Nielsen Dunbar

Carl A. B. Pearson

Sam Clifford

Christopher Jarvis

Alexis Robert

Niel Hens

Pietro Coletti

Lloyd Chapman

normalise_weights_to_counts function

<dl><dt>sampled_participants</dt>
<dd>the sampled participants data.table
(must have <code>sampled.weight</code> plus the participant columns referenced
by <code>groupings</code>)</dd>
<dt>weighted_matrix</dt>
<dd>a rank-<code>2K</code> array of weighted contact counts</dd>
<dt>groupings</dt>
<dd>a list of grouping triples (see <code>resolve_groupings()</code>);
defaults to single-age, matching pre-existing single-grouping output</dd></dl>

Arguments

Normalise a weighted contact array to mean contacts per participant — normalise_weights_to_counts

<dl>

<dt>sampled_participants</dt>
<dd>the sampled participants data.table
(must have <code>sampled.weight</code> plus the participant columns referenced
by <code>groupings</code>)</dd>


<dt>weighted_matrix</dt>
<dd>a rank-<code>2K</code> array of weighted contact counts</dd>


<dt>groupings</dt>
<dd>a list of grouping triples (see <code>resolve_groupings()</code>);
defaults to single-age, matching pre-existing single-grouping output</dd>

</dl>

Normalise a weighted contact array to mean contacts per participant

normalise_weights_to_counts: Normalise a weighted contact array to mean contacts per participant

Description

Usage

Value

Arguments