medInnovationsDiffNet


A directed dynamic graph with 125 vertices and 18 time periods. The attributes
in the graph are static and described in <code><a rd-options="" href="/link/medInnovations?package=netdiffuseR&version=1.17.0" data-mini-rdoc="netdiffuseR::medInnovations">medInnovations</a></code>.


Empirical statistical analysis, visualization and simulation
of diffusion and contagion processes on networks. The package implements
algorithms for calculating network diffusion statistics such as transmission
rate, hazard rates, exposure models, network threshold levels, infectiousness
(contagion), and susceptibility. The package is inspired by work published in
Valente, et al., (2015) <DOI:10.1016/j.socscimed.2015.10.001>; Valente (1995)
<ISBN:9781881303213>, Myers (2000) <DOI:10.1086/303110>, Iyengar and others
(2011) <DOI:10.1287/mksc.1100.0566>, Burt (1987) <DOI:10.1086/228667>; among
others.

George Vega Yon

netdiffuseR

Analysis of Diffusion and Contagion Processes on Networks

medInnovationsDiffNet function

A <code><a rd-options="" href="/link/diffnet?package=netdiffuseR&version=1.17.0" data-mini-rdoc="netdiffuseR::diffnet">diffnet</a></code> class object.

Format


A directed dynamic graph with 125 vertices and 18 time periods. The attributes
in the graph are static and described in <code><a rd-options='' href='medInnovations'>medInnovations</a></code>.


A <code><a rd-options='' href='diffnet'>diffnet</a></code> class object.

medInnovationsDiffNet: `diffnet` version of the Medical Innovation data

Description

Arguments

Format

See Also