Directly specify estimated model parameters and their covariance matrix.

1 |

`coef` |
estimated coefficients. |

`vcov` |
estimated covariance matrix of the coefficients. |

`df` |
an optional specification of the degrees of freedom to be used in subsequent computations. |

When only estimated model parameters and the corresponding
covariance matrix is available for simultaneous inference
using `glht`

(for example, when only the results
but not the original data are available or, even worse, when the model
has been fitted outside R), function `parm`

sets up an
object `glht`

is able to compute on (mainly
by offering `coef`

and `vcov`

methods).

Note that the linear function in `glht`

can't
be specified via `mcp`

since the model terms
are missing.

An object of class `parm`

with elements

`coef` |
model parameters |

`vcov` |
covariance matrix of model parameters |

`df` |
degrees of freedom |

1 2 3 4 5 6 7 8 9 10 11 | ```
## example from
## Bretz, Hothorn, and Westfall (2002).
## On multiple comparisons in R. R News, 2(3):14-17.
beta <- c(V1 = 14.8, V2 = 12.6667, V3 = 7.3333, V4 = 13.1333)
Sigma <- 6.7099 * (diag(1 / c(20, 3, 3, 15)))
confint(glht(model = parm(beta, Sigma, 37),
linfct = c("V2 - V1 >= 0",
"V3 - V1 >= 0",
"V4 - V1 >= 0")),
level = 0.9)
``` |

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