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 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)
``` |

`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] |

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, separation.parameter = 0.2)
``` |

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