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.