Description Usage Arguments Value Author(s) Examples

Takes in only one set of variables (e.g., predictors) and produces a covariance monoplot.

1 | ```
cov.monoplot(X, ...)
``` |

`X` |
A (NxP) predictor matrix |

`...` |
Other arguments. Currently ignored |

The covariance monoplot of X

Opeoluwa F. Oyedele and Sugnet Gardner-Lubbe

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
if(require(pls))
data(oliveoil, package="pls")
Y = as.matrix(oliveoil$sensory, ncol=6)
dimnames(Y) = list(paste(c("G1","G2","G3","G4","G5","I1","I2","I3","I4",
"I5","S1","S2","S3","S4","S5","S6")),
paste(c("Yellow","Green","Brown","Glossy","Transp","Syrup")))
cov.monoplot(Y)
#cocktail data
if(require(SensoMineR))
data(cocktail, package="SensoMineR")
Y3 = as.matrix(senso.cocktail, ncol=13)
cov.monoplot(Y3)
``` |

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