slpm_gen: slpm_gen

In SparseLPM: The Sparse Latent Position Model for Nonnegative Interaction Data

Description

Generates the adjacency matrix adj of a SparseLPM by sampling both the data and model parameters from the posterior distribution.

Usage

slpm_gen(M, N, K, hyper_pars = NULL)

Arguments

M	Number of rows of adj.
N	Number of cols of adj.
K	Number of latent dimensions of the SparseLPM.
hyper_pars	A list defining the hyperparameters of the model. If left as NULL all the hyperparameters are initialised to 1. Otherwise, the list should contain three vectors of K positive values denoted delta, a_gamma and b_gamma, respectively.

Value

A list with components:

adj	Generated adjacency matrix.
U	Generated latent positions for senders.
V	Generated latent positions for receivers.
lambda	Latent variables attached to each of the edges, selecting which dimension determines the edge probability.
gamma	Vector of the Gaussian precisions associated to the latent dimensions.

Examples

set.seed(12345)
network <- slpm_gen(M = 10, N = 8, K = 2)

SparseLPM documentation built on May 2, 2019, 3:31 a.m.