Simulation of, and fitting models for, Generalised Network Autoregressive (GNAR) time series models which take account of network structure.  Such models are described in Knight et al. (2020) <doi:10.18637/jss.v096.i05>.

Methods for Fitting Network Time Series Models

package-ubuntu-20.04-r-4.0.5#cran#GNAR-1.1.1

<p>Seed numbers for reproducible random graphs.
</p>

<p><code>seed.nos</code> is a vector of length 10,000 containing integers.
</p>

g <- seedToNet(seed.nos[1], nnodes=35, graph.prob=0.15)
plot(g, vertex.label=colnames(gdpVTS), vertex.size=0)

package-ubuntu-20.04-r-4.0.5#cran#GNAR-1.1.1#docs#seed.nos

seed.nos

Description

Usage

Format

Examples

GNAR

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