Comparison Between Multiple Wavelet Variances

Displays plots of multiple wavelet variances of different time series accounting for CI values.

compare_wvar(
  ...,
  split = FALSE,
  add_legend = TRUE,
  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,
  ci_wv = NULL,
  point_cex = NULL,
  point_pch = NULL,
  names = NULL,
  cex_labels = 0.8
)

Arguments

...	One or more time series objects.
split	A boolean that, if TRUE, arranges the plots into a matrix-like format.
add_legend	A boolean that, if TRUE, adds a legend to the plot.
units	A string that specifies the units of time plotted on the x axes. Note: This argument will not be used if xlab is specified.
xlab	A string that gives a title for the x axes.
ylab	A string that gives a title for the y axes.
main	A string that gives an overall title for the plot.
col_wv	A string that specifies the color of the wavelet variance lines.
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).
ci_wv	A boolean that determines whether confidence interval polygons will be drawn.
point_cex	A double that specifies the size of each symbol to be plotted.
point_pch	A double that specifies the symbol type to be plotted.
names	A string that specifies the name of the WVAR objects.
cex_labels	A double that specifies the magnification of the labels (x and y).

Examples

set.seed(999)
n = 10^4
Xt = arima.sim(n = n, list(ar = 0.10))
Yt = arima.sim(n = n, list(ar = 0.35))
Zt = arima.sim(n = n, list(ar = 0.70))
Wt = arima.sim(n = n, list(ar = 0.95))

wv_Xt = wvar(Xt)
wv_Yt = wvar(Yt)
wv_Zt = wvar(Zt)
wv_Wt = wvar(Wt)

compare_wvar(wv_Xt, wv_Yt, wv_Zt, wv_Wt)