# Calculate the critical value of the GGL objective funciton.

### Description

gcrit() calculates the critical value of the GGL objective funciton. It is used to confirm that the GGL algorithm is converging.

### Usage

1 | ```
gcrit(theta, S, n, lam1, lam2, penalize.diagonal)
``` |

### Arguments

`theta` |
A list of pXp inverse covariance matrices. |

`S` |
A list of pXp empirical covariance matrices. |

`n` |
A vector of sample sizes to attribute to each of the K data matrices. n controls the relative weights of the classes: for example, with n==c(1,1), each class's theta will be penalized equally. |

`lam1` |
The tuning parameter for the graphical lasso penalty. |

`lam2` |
The tuning parameter for the group lasso penalty. |

`penalize.diagonal` |
Logical, determining whether the penalties will be applied to the diagonal elements of the theta matrices. |

### Details

A function called by GGL to calculate the critical value of the objective function.

### Value

crit, the critical value of the list of inverse covariance matrices.

### Author(s)

Patrick Danaher

### References

Patrick Danaher, Pei Wang and Daniela Witten (2011). The joint graphical lasso for inverse covariance estimation across multiple classes. http://arxiv.org/abs/1111.0324