Description Usage Arguments Details Value Author(s) See Also Examples

Produce `summary`

methods for class `"rcc"`

,
`"pls"`

and `"spls"`

.

1 2 3 4 5 6 7 8 9 10 11 | ```
## S3 method for class 'rcc'
summary(object, what = c("all", "communalities", "redundancy"),
cutoff = NULL, digits = 4, ...)
## S3 method for class 'pls'
summary(object, what = c("all", "communalities", "redundancy",
"VIP"), digits = 4, keep.var = FALSE, ...)
## S3 method for class 'spls'
summary(object, what = c("all", "communalities", "redundancy",
"VIP"), digits = 4, keep.var = FALSE, ...)
``` |

`object` |
object of class inheriting from |

`cutoff` |
real between 0 and 1. Variables with all correlations components below this cutoff in absolute value are not showed (see Details). |

`digits` |
integer, the number of significant digits to use when printing.
Defaults to |

`what` |
character string or vector. Should be a subset of |

`keep.var` |
boolean. If |

`...` |
not used currently. |

The information in the `rcc`

, `pls`

or `spls`

object is summarised, it includes:
the dimensions of `X`

and `Y`

data,
the number of variates considered, the canonical correlations (if `object`

of class `"rcc"`

)
and the (s)PLS algorithm used (if `object`

of class `"pls"`

or `"spls"`

) and
the number of variables selected on each of the sPLS components (if `x`

of class `"spls"`

).

`"communalities"`

in `what`

gives Communalities Analysis.
`"redundancy"`

display Redundancy Analysis.
`"VIP"`

gives the Variable Importance in the Projection (VIP)
coefficients fit by `pls`

or `spls`

.
If `what`

is `"all"`

, all are given.

For class `"rcc"`

, when a value to `cutoff`

is specified, the correlations
between each variable and the equiangular vector between
*X*- and *Y*-variates are computed. Variables with at least one correlation componente
bigger than `cutoff`

are showed. The defaults is `cutoff=NULL`

all the variables
are given.

The function `summary`

returns a list with components:

`ncomp` |
the number of components in the model. |

`cor` |
the canonical correlations. |

`cutoff` |
the cutoff used. |

`keep.var` |
list containing the name of the variables selected. |

`mode` |
the algoritm used in |

`Cm` |
list containing the communalities. |

`Rd` |
list containing the redundancy. |

`VIP` |
matrix of VIP coefficients. |

`what` |
subset of |

`digits` |
the number of significant digits to use when printing. |

`method` |
method used: |

Sébastien Déjean, Ignacio González and Kim-Anh Lê Cao.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
## summary for objects of class 'rcc'
data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene
nutri.res <- rcc(X, Y, ncomp = 3, lambda1 = 0.064, lambda2 = 0.008)
more <- summary(nutri.res, cutoff = 0.65)
## summary for objects of class 'pls'
data(linnerud)
X <- linnerud$exercise
Y <- linnerud$physiological
linn.pls <- pls(X, Y)
more <- summary(linn.pls)
## summary for objects of class 'spls'
data(liver.toxicity)
X <- liver.toxicity$gene
Y <- liver.toxicity$clinic
toxicity.spls <- spls(X, Y, ncomp = 3, keepX = c(50, 50, 50),
keepY = c(10, 10, 10))
more <- summary(toxicity.spls, what = "redundancy", keep.var = TRUE)
``` |

```
Loading required package: MASS
Loading required package: lattice
Loading required package: ggplot2
Loaded mixOmics 6.3.2
Thank you for using mixOmics!
How to apply our methods: http://www.mixOmics.org for some examples.
Questions or comments: email us at mixomics[at]math.univ-toulouse.fr
Any bugs? https://bitbucket.org/klecao/package-mixomics/issues
Cite us: citation('mixOmics')
Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE
3: .onUnload failed in unloadNamespace() for 'rgl', details:
call: fun(...)
error: object 'rgl_quit' not found
```

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