| QuantileQuantilePlots | R Documentation |
Produce quantile-quantile plots for the normal, inverse Gaussian, generalized hyperbolic Student-t and the generalized lambda distributions.
qqnormPlot(x, labels = TRUE, col = "steelblue", pch = 19,
title = TRUE, mtext = TRUE, grid = FALSE, rug = TRUE,
scale = TRUE, ...)
qqnigPlot(x, labels = TRUE, col = "steelblue", pch = 19,
title = TRUE, mtext = TRUE, grid = FALSE, rug = TRUE,
scale = TRUE, ...)
qqghtPlot(x, labels = TRUE, col = "steelblue", pch = 19,
title = TRUE, mtext = TRUE, grid = FALSE, rug = TRUE,
scale = TRUE, ...)
qqgldPlot(x, labels = TRUE, col = "steelblue", pch = 19,
title = TRUE, mtext = TRUE, grid = FALSE, rug = TRUE,
scale = TRUE, ...)
x |
an object of class |
labels |
a logical flag, should the plot be returned with default labels and
decorated in an automated way? By default |
col |
the color for the series. In the univariate case use just a color
name like the default, |
pch |
an integer value, by default 19. Which plot character should be used in the plot? |
title |
a logical flag, by default |
mtext |
a logical flag, by default |
grid |
a logical flag, should a grid be added to the plot? By default
|
rug |
a logical flag, by default |
scale |
a logical flag, by default |
... |
optional arguments passed to |
qqnormPlot produces a tailored Normal quantile-quantile plot.
qqnigPlot produces a tailored NIG quantile-quantile plot.
qqghtPlot produces a tailored GHT quantile-quantile plot.
qqgldPlot produces a tailored GLD quantile-quantile plot.
a list containing some of the quantities computed for the plot, invisibly. Currently contains the following components:
x |
the quantiles of the reference distribution, used for the x-axis, |
y |
the (possibly scaled) ordered values of the time series, used for the y-axis. |
The list has attribute "control" containing the parameters of
the fitted distribution.
Diethelm Wuertz for the Rmetrics R-port.
seriesPlot,
returnPlot,
cumulatedPlot,
drawdownPlot
histPlot,
densityPlot,
logDensityPlot
boxPlot,
boxPercentilePlot
acfPlot,
pacfPlot,
teffectPlot,
lacfPlot
scalinglawPlot
returnSeriesGUI
## data
data(LPP2005REC, package = "timeSeries")
SPI <- LPP2005REC[, "SPI"]
plot(SPI, type = "l", col = "steelblue", main = "SP500")
abline(h = 0, col = "grey")
qqnormPlot(SPI)
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