fboot_plot: Plot the robustness of a functional clustering evaluated by...
In functClust: Functional Clustering of Redundant Components of a System

Description Usage Arguments Details Value References Examples

Evaluate by bootstrapping the robustness of a functional clustering to perturbations of data. The perturbed data can be the number of assemblages taken into account, or the number of performances taken into account.

1 2	fboot_plot(fres, lboot, main = "", opt.crit = "Jaccard", opt.var = c("assemblages", "performances"))

`fres`	an object resulting from a functional clustering obtained using the function `fclust`.
`lboot`	an object resulting from a functional clustering obtained using the function `fclust`.
`main`	a string, used as main title for all plots.
`opt.crit`	an object resulting from a functional clustering obtained using the function `fclust`.
`opt.var`	an object resulting from a functional clustering obtained using the function `fclust`.

The trees obtained by bootstrapping of performances to omit are compared to the reference tree obtained with all components using different criteria : "Czekanowski_Dice", "Folkes_Mallows", "Jaccard", "Kulczynski", "Precision", "Rand", "Recall", "Rogers_Tanimoto", "Russel_Rao", "Sokal_Sneath1" and "Sokal_Sneath2" index. For more informations, see the notice of R-package clusterCrit.

a list of lists, each containing a matrix by clustering index.

Package "clusterCrit": Clustering Indices, by Bernard Desgraupes (University of Paris Ouest - Lab Modal'X)

# Plot the significance of each component within each components cluster

layout(matrix(c(1,2,3,4), nrow = 2, ncol = 2, byrow = TRUE))
fboot_plot(fres  = CedarCreek.2004.2006.res,
           lboot = CedarCreek.2004.2006.boot.assemblages,
           main  = "BioDIV2",
           opt.var = "assemblages", opt.crit = "Jaccard")
layout(1)