plotFANOVA {fdANOVA} | R Documentation |
Plot Univariate Functional Data
Description
Univariate functional observations with or without indication of groups as well as mean functions of samples are plotted. We assume that univariate functional observations are observed on a common grid of
design time points equally spaced in
(see Section 3.1 of the vignette file,
vignette("fdANOVA", package = "fdANOVA")
).
Usage
plotFANOVA(x, group.label = NULL, int = NULL, separately = FALSE,
means = FALSE, smooth = FALSE, ...)
Arguments
x |
a |
group.label |
a character vector containing group labels. Its default value means that all functional observations are drawn without division into groups. |
int |
a vector of two elements representing the interval |
separately |
a logical indicating how groups are drawn. If |
means |
a logical indicating whether to plot only group mean functions. |
smooth |
a logical indicating whether to plot reconstructed data via smoothing splines instead of raw data. |
... |
additional arguments not used. |
Author(s)
Tomasz Gorecki, Lukasz Smaga
See Also
fanova.tests
, fmanova.ptbfr
, fmanova.trp
Examples
# Some of the examples may run some time.
# gait data (both features)
library(fda)
gait.data.frame <- as.data.frame(gait)
x.gait <- vector("list", 2)
x.gait[[1]] <- as.matrix(gait.data.frame[, 1:39])
x.gait[[2]] <- as.matrix(gait.data.frame[, 40:78])
# vector of group labels
group.label.gait <- rep(1:3, each = 13)
plotFANOVA(x = x.gait[[1]], int = c(0.025, 0.975))
plotFANOVA(x = x.gait[[1]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975))
plotFANOVA(x = x.gait[[1]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), separately = TRUE)
plotFANOVA(x = x.gait[[1]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), means = TRUE)
plotFANOVA(x = x.gait[[1]], int = c(0.025, 0.975), smooth = TRUE)
plotFANOVA(x = x.gait[[1]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), smooth = TRUE)
plotFANOVA(x = x.gait[[1]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), separately = TRUE, smooth = TRUE)
plotFANOVA(x = x.gait[[1]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), means = TRUE, smooth = TRUE)
plotFANOVA(x = x.gait[[2]], int = c(0.025, 0.975))
plotFANOVA(x = x.gait[[2]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975))
plotFANOVA(x = x.gait[[2]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), separately = TRUE)
plotFANOVA(x = x.gait[[2]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), means = TRUE)
plotFANOVA(x = x.gait[[2]], int = c(0.025, 0.975), smooth = TRUE)
plotFANOVA(x = x.gait[[2]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), smooth = TRUE)
plotFANOVA(x = x.gait[[2]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), separately = TRUE, smooth = TRUE)
plotFANOVA(x = x.gait[[2]], group.label = as.character(group.label.gait),
int = c(0.025, 0.975), means = TRUE, smooth = TRUE)
# Canadian Weather data (both features)
library(fda)
x.CW <- vector("list", 2)
x.CW[[1]] <- CanadianWeather$dailyAv[,,1]
x.CW[[2]] <- CanadianWeather$dailyAv[,,2]
# vector of group labels
group.label.CW <- rep(c("Eastern", "Western", "Northern"), c(15, 15, 5))
plotFANOVA(x = x.CW[[1]])
plotFANOVA(x = x.CW[[1]], group.label = as.character(group.label.CW))
plotFANOVA(x = x.CW[[1]], group.label = as.character(group.label.CW),
separately = TRUE)
plotFANOVA(x = x.CW[[1]], group.label = as.character(group.label.CW),
means = TRUE)
plotFANOVA(x = x.CW[[1]], smooth = TRUE)
plotFANOVA(x = x.CW[[1]], group.label = as.character(group.label.CW),
smooth = TRUE)
plotFANOVA(x = x.CW[[1]], group.label = as.character(group.label.CW),
separately = TRUE, smooth = TRUE)
plotFANOVA(x = x.CW[[1]], group.label = as.character(group.label.CW),
means = TRUE, smooth = TRUE)
plotFANOVA(x = x.CW[[2]])
plotFANOVA(x = x.CW[[2]], group.label = as.character(group.label.CW))
plotFANOVA(x = x.CW[[2]], group.label = as.character(group.label.CW),
separately = TRUE)
plotFANOVA(x = x.CW[[2]], group.label = as.character(group.label.CW),
means = TRUE)
plotFANOVA(x = x.CW[[2]], smooth = TRUE)
plotFANOVA(x = x.CW[[2]], group.label = as.character(group.label.CW),
smooth = TRUE)
plotFANOVA(x = x.CW[[2]], group.label = as.character(group.label.CW),
separately = TRUE, smooth = TRUE)
plotFANOVA(x = x.CW[[2]], group.label = as.character(group.label.CW),
means = TRUE, smooth = TRUE)