rmfanova (version 0.1.0)

pointwise_sample_mean_fun: Pointwise sample mean functions

Description

The function pointwise_sample_mean_fun() calculates and draws the pointwise sample mean functions.

Usage

pointwise_sample_mean_fun(
  x,
  plot = TRUE,
  values = FALSE,
  type = "l",
  lty = 1,
  main = "Sample mean functions",
  ...
)

Value

If values = TRUE, a matrix of values of the pointwise sample mean functions.

Arguments

x

a list of length \(\ell\) with elements being \(n\times p\) matrices of data corresponding to \(n\) functional observations measured in \(p\) design time points under given experimental conditions.

plot

a logical indicating of whether to draw the values of the pointwise sample mean functions. The default is TRUE.

values

a logical indicating of whether to return the values of the pointwise sample mean functions. The default is FALSE.

type

1-character string giving the type of plot desired, the same as in the matplot() function. The default is "l" for lines.

lty

vector of line types, the same as in the matplot() function. The default is 1 (solid lines).

main

a main title for the plot, the same as in the plot() function. The default is Sample mean functions.

...

other graphical parameters, the same as in the matplot() function.

References

Kurylo K., Smaga L. (2023) Functional repeated measures analysis of variance and its application. Preprint https://arxiv.org/abs/2306.03883

Examples

# preparation of the DTI data set, for details see Kurylo and Smaga (2023)
library(refund)
data(DTI)
# MS patients
DTI_ms <- DTI[DTI$case == 1, ]
miss_data <- c()
for (i in 1:340) if (any(is.na(DTI_ms$cca[i, ]))) miss_data <- c(miss_data, i)
DTI_ms <- DTI_ms[-miss_data, ]
DTI_ms_2 <- DTI_ms[DTI_ms$Nscans == 4, ]
xx <- vector("list", 4)
for (i in 1:4) {
  xx[[i]] <- DTI_ms_2$cca[DTI_ms_2$visit == i, ]
}
xx[[1]] <- xx[[1]][-14, ]
xx[[3]] <- xx[[3]][-14, ]
yy <- xx
for (i in seq_len(4)) yy[[i]] <- yy[[i]][1:17, ]
# sample mean functions
oldpar <- par(mfrow = c(1, 1), mar = c(4, 4, 2, 0.1))
pointwise_sample_mean_fun(yy, values = FALSE,
                          col = 1:4, xlab = "t", ylab = "FA", xaxt = "n")
axis(1, c(1, 15, 30, 45, 60, 75, 93), labels = c(1, 15, 30, 45, 60, 75, 93))
legend(x = 36, y = 0.64, legend = 1:4, lty = 1, col = 1:4, title = "Visit")
par(oldpar)