"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, ...)
GMWM
objectboolean
that indicates whether the decomposed processes should be plotted or notstring
that determines the graph background. It can be 'grey'
or 'white'
.boolean
that indicates whether the confidence interval should be plotted.double
that ranges from 0 to 1 that controls the transparency of the graph.boolean
that indicates whether the graph should be black and white color scheme.string
that indicates the color of the confidence interval (e.g. black, red, #003C7D, etc.)vector
of string
that indicates the type of lines.vector
of string
that indicates the color of lines.vector
of integer
that indicates the size of points on lines.vector
of integer
that indicates the shape of points on lines.string
that indicates the title of the graph.integer
that indicates the size of title.integer
that indicates the size of label.integer
that indicates the size of tick mark.string
that indicates the label on x axis.string
that indicates the label on y axis.string
that indicates the title of legend.vector
of string
that indicates the labels on legend.double
that indicates the size of key (in centermeters) on legend.integer
that indicates the size of title on legend.integer
that indicates the size of key label on legend.# AR
set.seed(1336)
n = 200
x = gen.gts(AR1(phi = .1, sigma2 = 1) + AR1(phi = 0.95, sigma2 = .1), n)
mod = gmwm(AR1(), data=x, model.type="imu")
autoplot(mod)
mod = gmwm(2*AR1(), data = x)
autoplot(mod)
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