BLSM object obtained by applying the Procrustean version of the latent space model to the unweighted network whose adjacency matrix is example_adjacency_matrix. Further details concerning the simulation are contained in the BLSM object itself.
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BLSM object (blsm_obj
), i.e. a list containing:
Alpha
α values from the sampled iterations
Likelihood
Log-likelihood values from the sampled iterations
Iterations
Latent space coordinates from the sampled iterations. Latent positions are stored in a
3D array whose dimensions are given by (1: number of nodes, 2: space dimensionality, 3: number of iterations).
In the non-Procrustean framework the latent distances are given instead of the positions: another 3D array is returned, whose dimensions
are given by (1: number of nodes, 2: number of nodes, 3: number of iterations). The command needed in order to get the average values over the iterations for
either the positions or the distances is rowMeans(blsm_obj$Iterations, dims=2)
(see example below).
StartingPositions
Latent space coordinates right after the initialization step. In the non-Procrustean framework starting distances are given instead.
Matrix
Original matrices of the network (adjacency and BLSM weights)
Parameters
List of parameters specified during the call to estimate_latent_positions
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