simu.RDPG {changepoints} R Documentation

## Simulate a dot product graph (without change point).

### Description

Simulate a dot product graph (without change point). The generated data is a matrix with each column corresponding to the vectorized adjacency (sub)matrix at a time point. For example, if the network matrix is required to be symmetric and without self-loop, only the strictly lower diagonal entries are considered.

### Usage

simu.RDPG(x_mat, n, symm = TRUE, self = FALSE)


### Arguments

 x_mat A numeric matrix representing the latent positions with horizontal axis being latent dimensions and vertical axis being nodes (each entry takes value in [0,1]). n A integer scalar representing the number of observations. symm A logic scalar indicating if adjacency matrices are required to be symmetric. self A logic scalar indicating if adjacency matrices are required to have self-loop.

### Value

A list with the following structure:

 obs_mat A matrix, with each column be the vectorized adjacency (sub)matrix. For example, if "symm = TRUE" and "self = FALSE", only the strictly lower triangular matrix is considered. graphon_mat Underlying graphon matrix.

Haotian Xu

### Examples

p = 20 # number of nodes
n = 50 # sample size for each segment
lat_dim_num = 5 # number of latent dimensions
set.seed(1)
x_mat = matrix(runif(p*lat_dim_num), nrow = p, ncol = lat_dim_num)
x_tilde_mat = matrix(runif(p*lat_dim_num), nrow = p, ncol = lat_dim_num)
y_mat = rbind(x_tilde_mat[1:floor(p/4),], x_mat[(floor(p/4)+1):p,])
rdpg1 = simu.RDPG(x_mat, n, symm = TRUE, self = FALSE)
rdpg2 = simu.RDPG(y_mat, n, symm = TRUE, self = FALSE)
data1_mat = rdpg1$obs_mat data2_mat = rdpg2$obs_mat
data_mat = cbind(data1_mat, data2_mat)


[Package changepoints version 1.1.0 Index]