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Bootstrap-style analogue of the MCMC gof_plot: draws nsim simulated networks from the fitted ALS model, computes the standard network statistics (sd.rowmean, sd.colmean, dyad.dep, cycle.dep, trans.dep for unipartite; sd.rowmean, sd.colmean, four.cycles for bipartite) on each replicate, and overlays the observed value on a histogram of replicate values.

Usage

gof_plot.ame_als(fit, nsim = 100, seed = NULL, ...)

Arguments

fit

an ame_als fit.

nsim

integer; number of replicates (default 100).

seed

optional RNG seed.

...

reserved.

Value

A ggplot (or patchwork) object.

Details

Uses simulate.ame_als for the replicates and is therefore conditional on the fitted point estimates: the noise is resampled, but mu, beta, a, b, U, V are held fixed. The MCMC gof_plot.ame also averages over posterior movement in those parameters.