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

Computes the (normalized or relative) profile likelihood for the parameters of a discrimination test, plots the normalized profile likelihood.

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`fitted` |
a |

`x` |
a |

`object` |
a |

`parm` |
currently not used |

`method` |
the type of spline to be used in approximating the
profile likelhood curve (trace)—se |

`n` |
the number of spline interpolations to use in plotting the profile likelihood curve (trace) |

`level` |
for |

`fig` |
logical: should the normalized profile likelihoods be plotted? |

`...` |
For |

`confint`

returns the confidence interval computed in
`discrim`

possibly at another level. The statistic used to
compute the confidence interval is therefore determined in the
`discrim`

call and may not be the likelihood root.

The likelihood profile is extracted from the `discrim`

object fitted with `statistic = "likelihood"`

.

For `profile`

:
An object of class `"profile.discrim", "data.frame"`

—a
`data.frame`

with two columns giving
the value of the parameter and the corresponding value of the profile
likelihood.

For `plot`

:
The profile object is returned invisibly.

For `confint`

:

A 3x2 matrix with columns named `"lower", "upper"`

giving the
lower and upper (100 * `level`

)% confidence interval for the
parameters named in the rows.

Rune Haubo B Christensen and Per Bruun Brockhoff

Brockhoff, P.B. and Christensen R.H.B. (2010). Thurstonian models for sensory discrimination tests as generalized linear models. Food Quality and Preference, 21, pp. 330-338.

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