robust_eda {wv}

Comparison between classical and robust Wavelet Variances

Description

Displays a plot of the wavelet variances (classical and robust) for a given time series accounting for CI values.

Usage

robust_eda(
  x,
  eff = 0.6,
  units = NULL,
  xlab = NULL,
  ylab = NULL,
  main = NULL,
  col_wv = NULL,
  col_ci = NULL,
  nb_ticks_x = NULL,
  nb_ticks_y = NULL,
  legend_position = NULL,
  ...
)

Arguments

x

A time series objects.

eff

An integer that specifies the efficiency of the robust estimator.

units

A string that specifies the units of time plotted on the x axis.

xlab

A string that gives a title for the x axis.

ylab

A string that gives a title for the y axis.

main

A string that gives an overall title for the plot.

col_wv

A string that specifies the color of the wavelet variance line.

col_ci

A string that specifies the color of the confidence interval shade.

nb_ticks_x

An integer that specifies the maximum number of ticks for the x-axis.

nb_ticks_y

An integer that specifies the maximum number of ticks for the y-axis.

legend_position

A string that specifies the position of the legend (use legend_position = NA to remove legend).

...

Additional arguments affecting the plot.

Value

Plot of wavelet variance and confidence interval for each scale.

Author(s)

Stephane Guerrier, Nathanael Claussen, and Justin Lee

Examples

set.seed(999)
n = 10^4
Xt = rnorm(n)
wv = wvar(Xt)

plot(wv)
plot(wv, main = "Simulated white noise", xlab = "Scales")
plot(wv, units = "sec", legend_position = "topright")
plot(wv, col_wv = "darkred", col_ci = "pink")