# data.simulation.factors: Simulates subspace clustering data with shared factors In varclust: Variables Clustering

## Description

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.

## Usage

 ```1 2 3``` ```data.simulation.factors(n = 100, SNR = 1, K = 10, numb.vars = 30, numb.factors = 10, min.dim = 1, max.dim = 2, equal.dims = TRUE, separation.parameter = 0.1) ```

## 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. `numb.factors` An integer, number of factors from which subspaces basis will be drawn. `min.dim` An integer, minimal dimension of 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 [min.dim,max.dim]. `equal.dims` A boolean, if TRUE (value set by default) all clusters are of the same dimension. `separation.parameter` a numeric, coefficients of variables in each subspace basis are drawn from range [separation.parameter,1]

## Value

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

## Examples

 ```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, separation.parameter = 0.2) ```

varclust documentation built on June 27, 2019, 5:08 p.m.