# perm.plot: Plot partial p-values In fdcov: Analysis of Covariance Operators

## Description

`perm.plot` plots all of the partial comparison p-values in a matrix.

## Usage

 `1` ```perm.plot(p, k, lab = NULL, save = FALSE, name = "pvalues.eps") ```

## Arguments

 `p` Output of function perm.test, if part = TRUE. `k` Number of groups, must be greater than 2. `lab` Group labels. Defaults to 1, 2, ..., k. `save` Boolean variable that indicates if the plot must be saved as an .eps. Defaults to FALSE. `name` If `save` is TRUE, this is the filename of the plot. Defaults to `pvalues.eps`.

## Value

`perm.plot` plots the partial p-values in a matrix.

## Author(s)

Alessandra Cabassi [email protected]

## References

Pigoli, Davide, John A. D. Aston, Ian L. Dryden, and Piercesare Secchi (2014). "Distances and inference for covariance operators." Biometrika: 101(2):409–422.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```## Not run: ## Phoneme data library(fdcov) library(fds) # Create data set data(aa); data(ao); data(dcl);data(iy);data(sh) dat=cbind(aa\$y[,1:20],ao\$y[,1:20],dcl\$y[,1:20],iy\$y[,1:20],sh\$y[,1:20]) dat=t(dat) grp=c(rep(1,20),rep(2,20),rep(3,20),rep(4,20),rep(5,20)) # Test the equality of the covariance operators p=ksample.perm(dat,grp,iter=100,only.glob=FALSE) # Plot partial p-values perm.plot(p,5, lab=c('aa','ao','dcl','iy','sh')) ## End(Not run) ```

fdcov documentation built on Dec. 23, 2017, 5:45 p.m.