Description Usage Arguments Value

Estimate the covariance matrix Sigma = C(A otimes B)C using kpcor or MN algorithm

1 2 |

`E` |
Matrix of dimension rc x n, each column is a (vectorized) residual vector |

`r` |
The number of "rows" of the inverse vectorized columns of E |

`type` |
One of "kpcor" and "mn", indicating which algorithm to use |

`restr` |
Allows the user to impose the matrix A or B to be diagonal. "N" for no restriction, "A" for diagonal A, "B" for diagonal B, and "AB" for both (only for kpcor). |

`tol` |
Algorithm terminates when an iteration increases the log-likelihood less than tol |

`maxiter` |
The maximum number of iterations the algorithm runs if not converging before |

`verbose` |
Print additional info about iterates if TRUE (only for kpcor) |

List with MLEs of the parameters A, B and D (D = inv(C), only for kpcor), log-likelihood at the final iterates, and the numver of iterations performed.

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