Description Usage Arguments Value Side Effects References See Also Examples

Find and optionally plot the marginal (profile) likelihood for alpha
for a transformation model of the form `log(y + alpha) ~ x1 + x2 + ...`

.

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`object` |
Fitted linear model object, or formula defining the untransformed
model that is |

`...` |
If |

`alpha` |
Set of values for the transformation parameter, alpha. |

`plotit` |
Should plotting be done? |

`interp` |
Should the marginal log-likelihood be interpolated with a spline
approximation? (Default is |

`xlab` |
as for |

`ylab` |
as for |

`data` |
optional |

List with components `x`

(for alpha) and `y`

(for the marginal
log-likelihood values).

A plot of the marginal log-likelihood is produced, if requested, together with an approximate mle and 95% confidence interval.

Venables, W. N. and Ripley, B. D. (2002)
*Modern Applied Statistics with S.* Fourth edition. Springer.

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