Description Usage Arguments Value See Also Examples

Generates *β* estimates for MLE using a conditioning approach with
patterning support.

1 |

`x` |
An |

`y` |
The |

`z` |
A |

`pattern` |
An optional |

A list with the following components:

- Beta
The least-squares estimate of

*β*.- SE
The

*(P + F) x L*matrix with the*ij*th element being the standard error of*\hat{β}_ij*.- T
The

*(P + F) x L*matrix with the*ij*th element being the t-statistic based on*\hat{β}_ij*.- Covbeta
The estimated covariance matrix of the

*\hat{β}_ij*'s.- df
A

*p*-dimensional vector of the degrees of freedom for the*t*-statistics, where the*j*th component contains the degrees of freedom for the*j*th column of*\hat{β}*.- Sigmaz
The

*(Q - F) x (Q - F)*matrix*\hat{Σ}_z*.- Cx
The

*Q x Q*residual sum of squares and crossproducts matrix.

`bothsidesmodel.mle`

and `bsm.simple`

1 | ```
# NA
``` |

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