coffee

Case study pertaining to consumer emotions associations for a
variety of 12 coffee aromas. The participants were asked to complete each rating (i.e., rating the odor of 12 aromas on 15 emotion terms) on a 5-point rating scale.

datasets

Functions for the clustering of variables around Latent Variables, for 2-way or 3-way data. Each cluster of variables, which may be defined as a local or directional cluster, is associated with a latent variable. External variables measured on the same observations or/and additional information on the variables can be taken into account. A "noise" cluster or sparse latent variables can also be defined.

Evelyne Vigneau

ClustVarLV

Clustering of Variables Around Latent Variables

coffee function

An object of class <code>"array"</code> with 12 odors (mode 1), 84 subjects (mode 2) and 15 emotions (mode 3):<dl class="dl-horizontal">
<dt>odors</dt><dd>Vanilla, B.Rice, Lemon, Coffee.Flower, Cedar, Hazelnut,
Coriander.Seed, Honey, Medicine, Apricot, Earth, Hay</dd>
<dt>subjects</dt><dd>persons from Oniris</dd>
<dt>emotions</dt><dd>Amused, Angry, Calm, Disappointed, Disgusted,
Energetic, Excited, Free, Happy, Irritated,
Nostalgic, Surprised, Unique, Unpleasant and Well</dd>
</dl>

Format

coffee data — coffee

An object of class <code>"array"</code> with 12 odors (mode 1), 84 subjects (mode 2) and 15 emotions (mode 3):<dl class='dl-horizontal'>
<dt>odors</dt><dd>Vanilla, B.Rice, Lemon, Coffee.Flower, Cedar, Hazelnut,
Coriander.Seed, Honey, Medicine, Apricot, Earth, Hay</dd>
<dt>subjects</dt><dd>persons from Oniris</dd>
<dt>emotions</dt><dd>Amused, Angry, Calm, Disappointed, Disgusted,
Energetic, Excited, Free, Happy, Irritated,
Nostalgic, Surprised, Unique, Unpleasant and Well</dd>
</dl>

coffee: coffee data

Description

Usage

Arguments

Format

References

Examples