data.simulation: Simulating subspace clustering data

In psobczyk/public_varclust: Variable Clustering

Description

Generating data for simulation with a low-rank subspace structure: variables are clustered and each cluster has a low-rank representation

Usage

data.simulation(n = 100, SNR = 1, K = 10, numb.vars = 30, max.dim = 2,
  equal.dims = TRUE)

Arguments

n	an integer, number of individuals
SNR	a numeric, signal to noise ratio measured as variance of the variable, element of a subspace, to the variance of noise
K	an integer, number of subspaces
numb.vars	an integer, number of variables in each subspace
max.dim	an integer, if equal.dims is TRUE then max.dim is dimension of each subspace. If equal.dims is FALSE then subspaces dimensions are drawn from uniform distribution on [1,max.dim]
equal.dims	a boolean, if TRUE (value set by default) all clusters are of the same dimension

Value

A list consisting of:

X	matrix, generated data
signals	matrix, data without noise
dims	vector, dimensions of subspaces
factors	matrix, factors subspaces
s	vector, true partiton of variables

Examples

sim.data <- data.simulation()
sim.data2 <- data.simulation(n = 30, SNR = 2, K = 5, numb.vars = 20,
                             max.dim = 3, equal.dims = FALSE)

psobczyk/public_varclust documentation built on May 26, 2019, 10:33 a.m.