Phase Boxplot for Warping Functions

Compute a functional boxplot for warping functions, identifying the median, central 50% region, whiskers, and outliers based on functional depth.

Usage

phase.boxplot(karcher.result, factor = 1.5)

Arguments

karcher.result

An object of class karcher.mean.

factor

Whisker extension factor, analogous to the IQR multiplier in a classical boxplot (default 1.5).

Value

An object of class phase.boxplot with components:

median

Median warping function

median.index

Index of the median warp in the input

central.lower

Lower boundary of the central 50% region

central.upper

Upper boundary of the central 50% region

whisker.lower

Lower whisker

whisker.upper

Upper whisker

depths

Functional depth values for each warp

outlier.indices

Indices of outlying warps

factor

The whisker extension factor used

argvals

Grid points

call

The matched call

References

Sun, Y. and Genton, M.G. (2011). Functional boxplots. Journal of Computational and Graphical Statistics, 20(2):316–334.

See also

karcher.mean, warp.statistics

Examples

# \donttest{
set.seed(1)
t <- seq(0, 1, length.out = 50)
X <- matrix(0, 15, 50)
for (i in 1:15) X[i, ] <- sin(2 * pi * (t - i / 60))
fd <- fdata(X, argvals = t)
km <- karcher.mean(fd, max.iter = 5)
pb <- phase.boxplot(km)
pb
#> Phase Boxplot (Warping Functions)
#>   Grid points: 50 
#>   Curves: 15 
#>   Median index: 8 
#>   Outliers: 2 
#>   Factor: 1.5 
# }