# To get BIC as a model selection criterion

### Description

To get BIC as a model selection criterion from MCMC sampling results.

### Usage

1 | ```
canopy.BIC(sampchain,projectname,K,numchain,burnin,thin,pdf)
``` |

### Arguments

`sampchain` |
list of sampled trees returned by |

`projectname` |
name of project |

`K` |
number of subclones (vector) |

`numchain` |
number of MCMC chains with random initiations |

`burnin` |
burnin of MCMC chains |

`thin` |
MCMC chains thinning |

`pdf` |
whether a pdf plot of BIC should be generated, default to be TRUE |

### Value

BIC values (vector) for model selection with plot generated (pdf format).

### Author(s)

Yuchao Jiang yuchaoj@wharton.upenn.edu

### Examples

1 2 3 4 5 6 7 8 9 | ```
data(MDA231_sampchain)
sampchain = MDA231_sampchain
projectname = 'MD231'
K = 3:6
numchain = 20
burnin = 150
thin = 5
bic = canopy.BIC(sampchain = sampchain, projectname = projectname, K = K,
numchain = numchain, burnin = burnin, thin = thin)
``` |