| XbordeauxNA {plsRglm} | R Documentation |
Incomplete dataset for the quality of wine dataset
Description
Quality of Bordeaux wines (Quality) and four potentially predictive
variables (Temperature, Sunshine, Heat and
Rain).
The value of Temperature for the first observation was
remove from the matrix of predictors on purpose.
Format
A data frame with 34 observations on the following 4 variables.
- Temperature
a numeric vector
- Sunshine
a numeric vector
- Heat
a numeric vector
- Rain
a numeric vector
Source
P. Bastien, V. Esposito-Vinzi, and M. Tenenhaus. (2005). PLS generalised linear regression. Computational Statistics & Data Analysis, 48(1):17-46.
References
M. Tenenhaus. (2005). La regression logistique PLS. In J.-J. Droesbeke, M. Lejeune, and G. Saporta, editors, Modeles statistiques pour donnees qualitatives. Editions Technip, Paris.
Examples
data(XbordeauxNA)
str(XbordeauxNA)
[Package plsRglm version 1.5.1 Index]