data.simulation.factors: Simulating subspace clustering data (shared factors)
In psobczyk/public_varclust: Variable Clustering

Description Usage Arguments Value Examples

Generating data for simulation with a low-rank subspace structure: variables are clustered and each cluster has a low-rank representation. Factors that span subspaces are shared between clusters

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

`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
`numb.factors`	an integer, number of factors from which subspaces basis will be drawn
`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

A list consisting of:

`X`	matrix, generated data
`signals`	matrix, data without noise
`factors`	matrix, columns of which span subspaces
`indices`	list of vectors, indices of factors that span subspaces
`dims`	vector, dimensions of subspaces
`s`	vector, true partiton of variables

1
2
3

sim.data <- data.simulation.factors()
sim.data2 <- data.simulation.factors(n = 30, SNR = 2, K = 5, numb.vars = 20,
             numb.factors = 10, max.dim = 3, equal.dims = FALSE)