Description Usage Arguments Details Value

This function applies generalized least squares to estimate the unknown parameters of a linear model X = D beta + E, where X has dimension n by m, D has dimension n by k, and beta has dimension k by m.

1 |

`X` |
data matrix. |

`D` |
design matrix. |

`B.inv` |
inverse covariance matrix. |

**Example**

1 2 3 4 |

Returns the estimated parameters of the linear model, a matrix of dimensions k by m, where k is the number of columns of D, and m is the number of columns of X.

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