Description Usage Arguments Author(s) See Also Examples
Univariate functional observations with or without indication of groups as well as mean functions of samples are plotted. We assume that n univariate functional observations are observed on a common grid of \mathcal{T} design time points equally spaced in I=[a,b] (see Section 3.1 of the vignette file, vignette("fdANOVA", package = "fdANOVA")
).
1 2 |
x |
a \mathcal{T}\times n matrix of data, whose each column is a discretized version of a function and rows correspond to design time points. |
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 I=[a,b]. When it is not specified, it is determined by a number of design time points. |
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. |
Tomasz Gorecki, Lukasz Smaga
fanova.tests
, fmanova.ptbfr
, fmanova.trp
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | # 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)
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