winesOf3Colors | R Documentation |
winesOf3Colors
:
36 wines are evaluated on several dimensions organized in 4 blocks.
An additional mystery wine is provided
(to be projected as supplementary observation).
data("winesOf3Colors")
A list with one data frame with four blocks of data:
1
The descriptors (origin, color, varietal):
columns 1 to 3.
2
The price (in Dollars): column 4.
3
The chemistry properties: columns 5 to 8
4
The sensory properties: columns 9 to 17.
The (fictitious) wines come from 3 countries Argentina, Canada, and the USA. They also come in three different colors: Red, Rosé, and White. They are described by their characteristics, chemistry, and sensory properties. The mystery wine is a French red pinot noir that could be though as a "Bourgogne Rouge".
Hervé Abdi and Dominique Valentin
These data have been used to illustrate PLSC and CCA. See, e.g., (papers available from https://personal.utdallas.edu/~herve/)
Abdi H., Eslami, A., & Guillemot, V. (2018). Canonical correlation analysis (CCA). In R. Alhajj and J. Rokne (Eds.), Encyclopedia of Social Networks and Mining (2nd Edition). New York: Springer Verlag.
Abdi, H., & Williams, L.J. (2013). Partial least squares methods: Partial least squares correlation and partial least square regression. In: B. Reisfeld & A. Mayeno (Eds.), Methods in Molecular Biology: Computational Toxicology. New York: Springer Verlag. pp. 549-579.
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