fboxplot {rainbow} | R Documentation |
Functional bagplot and functional HDR boxplot
Description
Compute bivariate bagplot, functional bagplot and bivariate HDR boxplot, functional HDR boxplot.
Usage
fboxplot(data, plot.type = c("functional", "bivariate"),
type = c("bag", "hdr"), alpha = c(0.05, 0.5), projmethod = c("PCAproj","rapca"),
factor = 1.96, na.rm = TRUE, xlab = data$xname, ylab = data$yname,
shadecols = gray((9:1)/10), pointcol = 1, plotlegend = TRUE,
legendpos = "topright", ncol = 2, ...)
Arguments
data |
An object of class |
plot.type |
Version of boxplot. When |
type |
Type of boxplot. When |
alpha |
Coverage probability for the functional HDR boxplot. |
factor |
When |
na.rm |
Remove missing values. |
xlab |
A title for the x axis. |
ylab |
A title for the y axis. |
shadecols |
Colors for shaded regions. |
pointcol |
Color for outliers and mode. |
plotlegend |
Add a legend to the graph. |
legendpos |
Legend position. By default, it is the top right corner. |
ncol |
Number of columns in the legend. |
projmethod |
Method used for projection. |
... |
Other arguments. |
Details
The functional curves are first projected into a finite dimensional subspace via functional principal component decomposition.
For simiplicity, we choose the subspace as R^2
. Based on Tukey (1974)'s halfspace bagplot and Hyndman (1996)'s HDR boxplot, we order each data point in R^2
by data depth and data density.
Outliers are those that have either lowest depth (distance from the centre) or lowest density.
Value
Function produces a graphical plot.
Author(s)
Rob J Hyndman, Han Lin Shang. Please, report bugs and suggestions to hanlin.shang@anu.edu.au
References
J. W. Tukey (1974) "Mathematics and the picturing of data", Proceedings of the International Congress of Mathematicians, 2, 523-532, Canadian Mathematical Congress, Montreal.
P. Rousseeuw, I. Ruts and J. Tukey (1999) "The bagplot: A bivariate boxplot", The American Statistician, 53(4), 382-387.
R. J. Hyndman (1996) "Computing and graphing highest density regions", The American Statistician, 50(2), 120-126.
R. J. Hyndman and H. L. Shang (2010) "Rainbow plots, bagplots, and boxplots for functional data", Journal of Computational and Graphical Statistics, 19(1), 29-45.
Y. Sun and M. G. Genton (2011) "Functional boxplots", Journal of Computational and Graphical Statistics, 20(2), 316-334.
Y. Sun and M. G. Genton (2012) "Adjusted functional boxplots for spatio-temporal data visualization and outlier detection", Environmetrics, 23, 54-64.
Y. Sun and M. G. Genton (2012) "Functional median polish", Journal of Agricultural, Biological, and Environmental Statistics, 17, 354-376.
See Also
Examples
fboxplot(data = ElNino_OISST_region_1and2, plot.type = "functional",
type = "bag", projmethod="PCAproj")
fboxplot(data = ElNino_OISST_region_1and2, plot.type = "bivariate",
type = "bag", projmethod="PCAproj")