Skip to contents

Plot for Functional Regression Test Results

Source: R/plot-flm.R
plot.flm.Rd

The S3 methods autoplot.fanova() and plot.fanova() are methods for plotting results of functional analysis of variance tests. They visualize the functional data and the adjusted p-values obtained from the testing procedures for mean comparison of multiple groups. The plots highlight significant effects at two levels of significance, alpha1 and alpha2, using shaded areas.

Usage

# S3 method for class 'flm'
autoplot(
  object,
  xrange = c(0, 1),
  alpha1 = 0.05,
  alpha2 = 0.01,
  plot_adjpval = FALSE,
  col = c(1, grDevices::rainbow(dim(object$adjusted_pval_part)[1])),
  ylim = NULL,
  ylabel = "Functional Data",
  title = NULL,
  linewidth = 1,
  type = "l",
  ...
)

# S3 method for class 'flm'
plot(
  x,
  xrange = c(0, 1),
  alpha1 = 0.05,
  alpha2 = 0.01,
  plot_adjpval = FALSE,
  ylim = NULL,
  col = 1,
  ylab = "Functional Data",
  main = NULL,
  lwd = 0.5,
  type = "l",
  ...
)

Arguments

object, x

The object to be plotted. An object of class "IWTlm", usually, a result of a call to IWTlm.

xrange

A length-2 numeric vector specifying the range of the x-axis for the plots. Defaults to c(0, 1). This should match the domain of the functional data.

alpha1

A numeric value specifying the first level of significance used to select and display significant effects. Defaults to alpha1 = 0.05.

alpha2

A numeric value specifying the second level of significance used to select and display significant effects. Defaults to alpha2 = 0.01.

plot_adjpval

A boolean value specifying whether the plots of adjusted p-values should be displayed. Defaults to FALSE.

col

An integer specifying the color for the plot of functional data. Defaults to 1L.

ylim

A 2-length numeric vector specifying the range of the y-axis. Defaults to NULL, which determines automatically the range from functional data.

ylabel, ylab

A string specifying the label of the y-axis of the functional data plot. Defaults to "Functional Data".

title, main

A string specifying the title of the functional data plot. Defaults to NULL in which case no title is displayed.

linewidth, lwd

A numeric value specifying the width of the line for the functional data plot. Note that the line width for the adjusted p-value plot will be twice this value. Defaults to 0.5.

type

A string specifying the type of plot for the functional data. Defaults to "l" for lines.

...

Other arguments passed to specific methods. Not used in this function.

Value

The autoplot.flm() function creates a ggplot object that displays the functional data and the adjusted p-values. The significant intervals at levels alpha1 and alpha2 are highlighted in the plots. The plot.flm() function is a wrapper around autoplot.flm() that prints the plot directly.

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.

See also

IWTimage() for the plot of p-values heatmaps (for IWT).

Examples

temperature <- rbind(NASAtemp$milan[, 1:100], NASAtemp$paris[, 1:100])
groups <- c(rep(0, 22), rep(1, 22))

# Performing the IWT
IWT_result <- IWTlm(temperature ~ groups, B = 2L)
#> 
#> ── Point-wise tests ────────────────────────────────────────────────────────────
#> 
#> ── Interval-wise tests ─────────────────────────────────────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 2 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 3 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 4 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 5 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 6 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 7 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 8 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 9 out of 100 ────────────────────────
#> 
#> ── Creating the p-value matrix: end of row 10 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 11 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 12 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 13 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 14 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 15 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 16 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 17 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 18 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 19 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 20 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 21 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 22 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 23 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 24 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 25 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 26 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 27 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 28 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 29 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 30 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 31 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 32 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 33 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 34 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 35 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 36 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 37 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 38 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 39 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 40 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 41 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 42 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 43 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 44 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 45 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 46 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 47 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 48 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 49 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 50 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 51 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 52 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 53 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 54 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 55 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 56 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 57 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 58 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 59 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 60 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 61 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 62 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 63 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 64 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 65 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 66 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 67 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 68 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 69 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 70 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 71 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 72 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 73 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 74 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 75 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 76 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 77 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 78 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 79 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 80 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 81 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 82 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 83 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 84 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 85 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 86 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 87 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 88 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 89 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 90 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 91 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 92 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 93 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 94 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 95 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 96 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 97 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 98 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 99 out of 100 ───────────────────────
#> 
#> ── Creating the p-value matrix: end of row 100 out of 100 ──────────────────────
#> 
#> ── Interval-Wise Testing completed ─────────────────────────────────────────────

# Summary of the IWT results
summary(IWT_result)
#> $call
#> iwt_lm(formula = formula, dx = dx, n_perm = B, method = method, 
#>     recycle = recycle)
#> 
#> $ttest
#>             Minimum p-value    
#> (Intercept)               0 ***
#> groups                    0 ***
#> 
#> $R2
#>               Range of functional R-squared
#> Min R-squared                  0.0003189364
#> Max R-squared                  0.2476892354
#> 
#> $ftest
#>   Minimum p-value    
#> 1               0 ***
#> 

# Plot of the IWT results
plot(
  IWT_result,
  main = 'NASA data',
  plot_adjpval = TRUE,
  xlab = 'Day',
  xrange = c(1, 365)
)
#> Warning: Removed 100 rows containing missing values or values outside the scale range
#> (`geom_line()`).
#> Warning: Removed 100 rows containing missing values or values outside the scale range
#> (`geom_line()`).