em_aic {betaclust} | R Documentation |

## Akaike Information Criterion

### Description

Compute the AIC value for the optimal model.

### Usage

```
em_aic(llk, C, M, N, R, model_name = "K..")
```

### Arguments

`llk` |
Log-likelihood value. |

`C` |
Number of CpG sites. |

`M` |
Number of methylation states identified in a DNA sample. |

`N` |
Number of patients. |

`R` |
Number of DNA sample types collected from each patient. |

`model_name` |
Fitted mixture model. Options are "K..", "KN." and/or "K.R" (default = "K.."). |

### Details

Computes the AIC for a specified model given the log-likelihood, the dimension of the data, and the model names.

### Value

The AIC value for the selected model.

### See Also

[Package

*betaclust*version 1.0.3 Index]