fBoxplot {GET} | R Documentation |
Functional boxplot
Description
Functional boxplot based on central region computed by a specified measure.
The options of the measures can be found in central_region
.
Usage
fBoxplot(curve_sets, factor = 1.5, coverage = 0.5, ...)
Arguments
curve_sets |
A |
factor |
The constant factor to inflate the central region to produce a functional boxplot and determine fences for outliers. Default is 1.5 as in a classical boxplot. |
coverage |
A number between 0 and 1. The 100*coverage% central region will be calculated. A vector of values can also be provided, leading to the corresponding number of central regions. |
... |
Additional parameters to be passed to |
Examples
if(requireNamespace("fda", quietly=TRUE)) {
years <- paste(1:18)
curves <- fda::growth[['hgtf']][years,]
# Heights
cset1 <- curve_set(r = as.numeric(years),
obs = curves)
bp <- fBoxplot(cset1, coverage=0.50, type="area", factor=1)
plot(bp)
# Considering simultaneously heights and height differences
cset2 <- curve_set(r = as.numeric(years[-1]),
obs = curves[-1,] - curves[-nrow(curves),])
csets <- list(Height=cset1, Change=cset2)
res <- fBoxplot(csets, type='area', factor=1.5)
plot(res) + ggplot2::labs(x="Age (years)", y="")
}