wbread: The White Bread Data

In sensory: Simultaneous Model-Based Clustering and Imputation via a Progressive Expectation-Maximization Algorithm

Description

The white bread data is a liking study composed of 420 panelists and 12 products, labelled A,...,L to protect the identity of the manufacturer. Each panelist rated 6 white breads using the 9-point Hedonic scale.

Usage

data(wbread)

References

Browne, R.P., P.D. McNicholas, and C.J. Findlay (2013). A partial EM algorithm for clustering white breads. arXiv prerpeint arXiv:1302.6625.

Examples

data(wbread) # Loads the white bread data
head(wbread) # Displays the first six rows of the white bread data

Example output

Loading required package: Matrix
Loading required package: gtools
Loading required package: MASS
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
[1,]    9   NA    8    6   NA   NA   NA    9   NA    NA     4     8
[2,]    3   NA    8   NA    7   NA    8    7    8    NA    NA    NA
[3,]   NA    8    6    7   NA   NA   NA   NA    6     9     7    NA
[4,]   NA   NA    5    4   NA    6   NA    4    3     6    NA    NA
[5,]   NA   NA    7    7   NA   NA    8    7    6    NA     8    NA
[6,]   NA   NA   NA    8   NA   NA    3    4    8    NA     7     7

sensory documentation built on May 2, 2019, 4:01 p.m.