sample_dclvm {nett}

Sample from a DCLVM

Description

A DCLVM with K clusters has edges generated as

E[\,A_{ij} \mid x, \theta\,] \;\propto\; \theta_i \theta_j e^{- \|x_i - x_j\|^2}

where x_i = 2 e_{z_i} + w_i, e_k is the kth basis vector of R^d, w_i \sim N(0, I_d), and \{z_i\} \subset [K]^n. The proportionality constant is chosen such that the overall network has expected average degree \lambda. To calculate the scaling constant, we approximate E[e^{- \|x_i - x_j\|^2}] for i \neq j by generating random npairs \{z_i, z_j\} and average over them.

Usage

sample_dclvm(z, lambda, theta, npairs = NULL)

Arguments

z

a vector of cluster labels

lambda

desired average degree of the network

theta

degree parameter

npairs

number of pairs of \{z_i, z_j\}

Details

Sample form a degree-corrected latent variable model with Gaussian kernel

Value

Adjacency matrix of DCLVM