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 . Based on Tukey (1974)'s halfspace bagplot and Hyndman (1996)'s HDR boxplot, we order each data point in
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")