Description Usage Arguments Details Value Author(s) See Also Examples

Function that performs maximum likelihood estimation of the covariance matrix, with various types of assumptions on its structure.

1 2 | ```
covMLknown(Y, covMat = NULL, corMat = NULL, corType = "none",
varType = "none", nInit = 100)
``` |

`Y` |
Data |

`covMat` |
A positive-definite covariance |

`corMat` |
A positive-definite correlation |

`corType` |
A |

`varType` |
A |

`nInit` |
An |

The function gives the maximum likelihood estimate of the covariance matrix. The input matrix `Y`

assumes that the variables
are represented by the columns.

When simultaneously `covMat=NULL`

, `corMat=NULL`

, `corType="none"`

and `varType="none"`

the `covML`

-function is invoked and the regular maximum likelihood estimate of the covariance matrix is returned.

The maximum likelihood estimate of the covariance `matrix`

under the specified assumptions on its structure.

Wessel N. van Wieringen, Carel F.W. Peeters <[email protected]>

1 2 3 4 5 6 7 8 9 |

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