GenerateToyData {CJIVE} | R Documentation |

Generates two Simulated Datasets that follow JIVE Model using binary subject scores

```
GenerateToyData(
n,
p1,
p2,
JntVarEx1,
JntVarEx2,
IndVarEx1,
IndVarEx2,
jnt_rank = 1,
equal.eig = FALSE,
ind_rank1 = 2,
ind_rank2 = 2,
SVD.plots = TRUE,
Error = TRUE,
print.cor = TRUE
)
```

`n` |
integer for sample size, i.e. number of subjects |

`p1` |
integer for number of features/variables in first data set |

`p2` |
integer for number of features/variables in second data set |

`JntVarEx1` |
numeric between (0,1) which describes proportion of variance in the first data set which is attributable to the joint signal |

`JntVarEx2` |
numeric between (0,1) which describes proportion of variance in the second data set which is attributable to the joint signal |

`IndVarEx1` |
numeric between (0,1) which describes proportion of variance in the first data set which is attributable to the individual signal |

`IndVarEx2` |
numeric between (0,1) which describes proportion of variance in the second data set which is attributable to the individual signal |

`jnt_rank` |
integer for rank of the joint signal, i.e., number of joint components |

`equal.eig` |
logical (TRUE/FALSE) for whether components should contribute equal variance to signal matrices - default is FALSE |

`ind_rank1` |
integer for rank of the individual signal in first data set, i.e., number of joint components |

`ind_rank2` |
integer for rank of the individual signal in second data set, i.e., number of joint components |

`SVD.plots` |
logical (TRUE/FALSE) for whether plots of singular values from signal should be produced - used to confirm number of components |

`Error` |
logical (TRUE/FALSE) final data sets should be noise contaminated - default is FALSE; use TRUE to obtain pure signal datasets |

`print.cor` |
logical (TRUE/FALSE) for whether to print matrix of correlations between subject scores) |

A 'list' object which contains 1) list of signal matrices which additively comprise the simulated data sets, i.e. joint, individual, and error matrices for each data set; 2) list of simulated data sets (each equal to the sum of the matrices in part 1); 3) list of joint subject scores and individual subject scores for each data set, and 4) lsit of joint and individual loadings for each data set

```
ToyDat = GenerateToyData(n = 200, p1 = 2000, p2 = 1000, JntVarEx1 = 0.05, JntVarEx2 = 0.05,
IndVarEx1 = 0.25, IndVarEx2 = 0.25, jnt_rank = 1, equal.eig = FALSE,
ind_rank1 = 2, ind_rank2 = 3, SVD.plots = TRUE, Error = TRUE,
print.cor = TRUE)
```

[Package *CJIVE* version 0.1.0 Index]