Plot method for ITP results on functional ANOVA

plot method for class "ITPaov". Plotting function creating a graphical output of the ITP for the test on a functional analysis of variance: functional data, and ITP-adjusted p-values of the F-tests on the whole model and on each factor are plotted.

Usage

# S3 method for class 'ITPaov'
plot(
  x,
  xrange = c(0, 1),
  alpha1 = 0.05,
  alpha2 = 0.01,
  plot.adjpval = FALSE,
  ylim = range(x$data.eval),
  col = 1,
  ylab = "Functional Data",
  main = NULL,
  lwd = 1,
  pch = 16,
  ...
)

Arguments

x: The object to be plotted. An object of class "ITPaov", usually, a result of a call to ITPaovbspline.
xrange: Range of the x axis.
alpha1: First level of significance used to select and display significant effects. Default is alpha1 = 0.05.
alpha2: Second level of significance used to select and display significant effects. Default is alpha1 = 0.01. alpha1 and alpha2 are s.t. alpha2 < alpha1. Otherwise the two values are switched.
plot.adjpval: A logical indicating wether the plots of adjusted p-values have to be done. Default is plot_adjpval = FALSE.
ylim: Range of the y axis. Default is NULL, giving a plot with authomatic range for functional data.
col: Colors for the plot of functional data. Default is col = 1.
ylab: Label of y axis of the plot of functional data. Default is "Functional Data".
main: An overall title for the plots (it will be pasted to "Functional Data and F-test" for the first plot and to factor names for the other plots).
lwd: Line width for the plot of functional data. Default is lwd=1.
pch: Point character for the plot of adjusted p-values. Default is pch=16.
...: Additional plotting arguments that can be used with function plot, such as graphical parameters (see par).

Value

No value returned. The function produces a graphical output of the ITP results: the plot of the functional data and the one of the adjusted p-values. The portions of the domain selected as significant by the test at level alpha1 and alpha2 are highlighted in the plot of the adjusted p-value function and in the one of functional data by gray areas (light and dark gray, respectively). The first plot reports the gray areas corresponding to a significant F-test on the whole model. The remaining plots report the gray areas corresponding to significant F-tests on each factor (with colors corresponding to the levels of the factor).

References

Pini, A., & Vantini, S. (2017). Interval-wise testing for functional data. Journal of Nonparametric Statistics, 29(2), 407-424

Pini, A., Vantini, S., Colosimo, B. M., & Grasso, M. (2018). Domain‐selective functional analysis of variance for supervised statistical profile monitoring of signal data. Journal of the Royal Statistical Society: Series C (Applied Statistics) 67(1), 55-81.

Abramowicz, K., Hager, C. K., Pini, A., Schelin, L., Sjostedt de Luna, S., & Vantini, S. (2018). Nonparametric inference for functional‐on‐scalar linear models applied to knee kinematic hop data after injury of the anterior cruciate ligament. Scandinavian Journal of Statistics 45(4), 1036-1061.

Examples

temperature <- rbind(NASAtemp$milan,NASAtemp$paris)
groups <- c(rep(0,22),rep(1,22))

# Performing the ITP
ITP.result <- ITPaovbspline(temperature ~ groups,B=100,nknots=20,order=3)
#> 
#> ── First step: basis expansion ─────────────────────────────────────────────────
#> Swapping 'y' and 'argvals', because 'y' is  simpler,
#>   and 'argvals' should be;  now  dim(argvals) =  365 ;  dim(y) =  365 x 44 
#> 
#> ── Second step: joint univariate tests ─────────────────────────────────────────
#> Error in eval(predvars, data, env): object 'groups' not found

# Summary of the ITP results
summary(ITP.result)
#> Error: object 'ITP.result' not found

# Plot of the ITP results
graphics::layout(1)
plot(ITP.result)
#> Error: object 'ITP.result' not found

# All graphics on the same device
graphics::layout(matrix(1:4,nrow=2,byrow=FALSE))
plot(ITP.result,main='NASA data', plot_adjpval = TRUE,xlab='Day',xrange=c(1,365))
#> Error: object 'ITP.result' not found