| autoplot.gmwm | R Documentation | 
Creates a graph containing the empirical and theoretical wavelet variances constructed via GMWM.
## S3 method for class 'gmwm'
autoplot(object, process.decomp = FALSE,
  background = "white", CI = T, transparence = 0.1, bw = F,
  CI.color = "#003C7D", line.type = NULL, line.color = NULL,
  point.size = NULL, point.shape = NULL, title = NULL,
  title.size = 15, axis.label.size = 13, axis.tick.size = 11,
  axis.x.label = expression(paste("Scale ", tau)),
  axis.y.label = expression(paste("Wavelet Variance ", nu)),
  legend.title = "", legend.label = NULL, legend.key.size = 1,
  legend.title.size = 13, legend.text.size = 13, ...)
object | 
 A   | 
process.decomp | 
 A   | 
background | 
 A   | 
CI | 
 A   | 
transparence | 
 A   | 
bw | 
 A   | 
CI.color | 
 A   | 
line.type | 
 A   | 
line.color | 
 A   | 
point.size | 
 A   | 
point.shape | 
 A   | 
title | 
 A   | 
title.size | 
 An   | 
axis.label.size | 
 An   | 
axis.tick.size | 
 An   | 
axis.x.label | 
 A   | 
axis.y.label | 
 A   | 
legend.title | 
 A   | 
legend.label | 
 A   | 
legend.key.size | 
 A   | 
legend.title.size | 
 An   | 
legend.text.size | 
 An   | 
... | 
 other arguments passed to specific methods.  | 
A ggplot2 panel containing the graph of the empirical and theoretical wavelet variance under the constructed GMWM.
JJB, Wenchao
# AR set.seed(1336) n = 200 x = gen_gts(n, AR1(phi = .1, sigma2 = 1) + AR1(phi = 0.95, sigma2 = .1)) mod = gmwm(AR1(), data = x, model.type = "imu") autoplot(mod) mod = gmwm(2*AR1(), data = x) autoplot(mod)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.