KDEs: Generate an object of class 'KDEs'

In provenance: Statistical Toolbox for Sedimentary Provenance Analysis

Description

Convert a dataset of class distributional into an object of class KDEs for further processing by the summaryplot function.

Usage

KDEs(x, from = NA, to = NA, bw = NA, samebandwidth = TRUE,
  adaptive = TRUE, pch = NA, normalise = FALSE, log = FALSE, n = 512,
  ...)

Arguments

x	an object of class distributional
from	minimum limit of the x-axis.
to	maximum limit of the x-axis.
bw	the bandwidth of the kernel density estimates. If bw = NA, the bandwidth will be set automatically using botev()
samebandwidth	boolean flag indicating whether the same bandwidth should be used for all samples. If samebandwidth = TRUE and bw = NULL, then the function will use the median bandwidth of all the samples.
adaptive	boolean flag switching on the adaptive bandwidth modifier of Abramson (1982)
pch	(optional) symbol to be used to mark the sample points along the x-axis
normalise	boolean flag indicating whether or not the KDEs should all integrate to the same value.
log	boolean flag indicating whether the data should by plotted on a logarithmic scale.
n	horizontal resolution of the density estimates
...	optional parameters to be passed on to density

Value

an object of class KDEs, i.e. a list containing the following items:

kdes: a named list with objects of class KDE

from: the beginning of the common time scale

to: the end of the common time scale

themax: the maximum probability density of all the KDEs

pch: the plot symbol to be used by plot.KDEs

xlabel: the x-axis label to be used by plot.KDEs

See Also

KDE

Examples

data(Namib)
KDEs <- KDEs(Namib$DZ,0,3000,pch=NA)
summaryplot(KDEs,ncol=3)

provenance documentation built on April 24, 2018, 5:04 p.m.