# Simulated data - Scenario 1

### Description

Simulates the data as described in the reference provided below (Scenario 1).

### Usage

1 | ```
Scenario1(sigmak = 0.1)
``` |

### Arguments

`sigmak` |
Standard deviation of the error term |

### Value

Return a list made of the following items

`Y ` |
Matrix of simulated gene expression |

`X ` |
Matrix of simulated CGH |

`Xi ` |
True matrix of hidden states |

`A ` |
Empirical transition matrix |

`mu ` |
True vector of state specific mean |

`Sd ` |
True vector of state specific sd |

`coeff ` |
True matrix of association coefficients between gene expression and CGH probes |

`distance ` |
Vector of distance between CGH probes |

`disfix ` |
Length of the chromosome |

### Author(s)

Alberto Cassese

### References

Cassese A, Guindani M, Tadesse M, Falciani F, Vannucci M. A hierarchical Bayesian model for inference of copy number variants and their association to gene expression. Annals of Applied Statistics, 8(1), 148-175.

Cassese A, Guindani M, Vannucci M. A Bayesian integrative model for genetical genomics with spatially informed variable selection. Cancer Informatics.

### Examples

1 |