Repeatedly fits a latent trait model to a binary interaction network to return a probability matrix
FitMatching(list, N_runs = 10, maxit = 10000, method = "Nelder-Mead",
ExtraSettings = NULL)Network List
Number of start points for k2 and lambda to try. The best (maximum likelihood) half will be used to construct the probability matrix
Default = 10'000
Passed to optim, default = 'Nelder-Mead'
Other control settings to pass to optim()
Network list with added 'M_par',the best fitting parameters, 'M_ProbsMatrix', the probability matrix
The optimiser is started at values derived from the row-sums and column-sums of a CCA analysis, which correspond closely to latent traits by matching closely related species together.
The k2 and lambda parameters are started from points drawn from a uniform distribution 0:1.