Akin to ERGMs, goodness of fit testing is available to see whether auxiliary statistics are well captured by the model. The logic behind gof testing for network models is outlined in Hunter et al. (2008) and Lospinoso and Snijders (2019).
ans: An object of class "result.monan" resulting from an estimation with the function estimateMobilityNetwork() using the option deps = TRUE.
gofFunction: A gof function that specifies which auxiliary outcome should be used, e.g., "getIndegree" or "getTieWeights".
lvls: The values for which the gofFunction should be calculated/plotted.
simulations: outdated parameter, no need to specify
x: An object of class "gof.stats.monan".
...: Additional plotting parameters, use discouraged.
Returns
The function gofMobilityNetwork returns a list containing (1) the observed values of the auxiliary statistics and (2) a list of the simulated values of the auxiliary statistics.
The function plot.gof.stats.monan returns violin plots of the gof tests with observed values superimposed in red.
Hunter, D. R., Goodreau, S. M., & Handcock, M. S. (2008). Goodness of fit of social network models. Journal of the american statistical association, 103(481), 248-258.
Lospinoso, J., & Snijders, T. A. (2019). Goodness of fit for stochastic actor-oriented models. Methodological Innovations, 12(3).