Description Usage Arguments Details References See Also Examples
Plot a dataset as a Cumulative Age Distribution (CAD), also known as a ‘empirical cumulative distribution function’.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | cad(x, ...)
## Default S3 method:
cad(x, pch = NA, verticals = TRUE,
xlab = "age [Ma]", colmap = "heat.colors", col = "black",
hide = NULL, ...)
## S3 method for class 'detritals'
cad(x, pch = NA, verticals = TRUE,
xlab = "age [Ma]", colmap = "heat.colors", hide = NULL, ...)
## S3 method for class 'UPb'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", type = 4, cutoff.76 = 1100, cutoff.disc = c(-15,
5), common.Pb = 0, hide = NULL, ...)
## S3 method for class 'PbPb'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", common.Pb = 1, hide = NULL, ...)
## S3 method for class 'ArAr'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", i2i = FALSE, hide = NULL, ...)
## S3 method for class 'KCa'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", i2i = FALSE, hide = NULL, ...)
## S3 method for class 'ThU'
cad(x, pch = NA, verticals = TRUE, xlab = "age [ka]",
col = "black", i2i = FALSE, detritus = 0, Th02 = c(0, 0),
Th02U48 = c(0, 0, 1e+06, 0, 0, 0, 0, 0, 0), hide = NULL, ...)
## S3 method for class 'ReOs'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", i2i = TRUE, hide = NULL, ...)
## S3 method for class 'SmNd'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", i2i = TRUE, hide = NULL, ...)
## S3 method for class 'RbSr'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", i2i = TRUE, hide = NULL, ...)
## S3 method for class 'LuHf'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", i2i = TRUE, hide = NULL, ...)
## S3 method for class 'UThHe'
cad(x, pch = NA, verticals = TRUE, xlab = "age [Ma]",
col = "black", hide = NULL, ...)
## S3 method for class 'fissiontracks'
cad(x, pch = NA, verticals = TRUE,
xlab = "age [Ma]", col = "black", hide = NULL, ...)
|
x |
a numerical vector OR an object of class |
... |
optional arguments to the generic |
pch |
plot character to mark the beginning of each CAD step |
verticals |
logical flag indicating if the horizontal lines of the CAD should be connected by vertical lines |
xlab |
x-axis label |
colmap |
an optional string with the name of one of |
col |
colour to give to single sample datasets (not applicable
if |
hide |
vector with indices of aliquots that should be removed from the plot. |
type |
scalar indicating whether to plot the
^{207}Pb/^{235}U age ( |
cutoff.76 |
the age (in Ma) below which the
^{206}Pb/^{238}U-age and above which the
^{207}Pb/^{206}Pb-age is used. This parameter is
only used if |
cutoff.disc |
two element vector with the maximum and minimum
percentage discordance allowed between the
^{207}Pb/^{235}U and ^{206}Pb/^{238}U
age (if ^{206}Pb/^{238}U < cutoff.76) or between
the ^{206}Pb/^{238}U and
^{207}Pb/^{206}Pb age (if
^{206}Pb/^{238}U > cutoff.76). Set
|
common.Pb |
apply a common lead correction using one of three methods:
|
i2i |
‘isochron to intercept’: calculates the initial (aka
‘inherited’, ‘excess’, or ‘common’)
^{40}Ar/^{36}Ar, ^{40}Ca/^{44}Ca,
^{207}Pb/^{204}Pb, ^{87}Sr/^{86}Sr,
^{143}Nd/^{144}Nd, ^{187}Os/^{188}Os,
^{230}Th/^{232}Th or ^{176}Hf/^{177}Hf
ratio from an isochron fit. Setting |
detritus |
detrital ^{230}Th correction (only applicable
when
|
Th02 |
2-element vector with the assumed initial
^{230}Th/^{232}Th-ratio of the detritus and its
standard error. Only used if |
Th02U48 |
9-element vector with the measured composition of
the detritus, containing |
Empirical cumulative distribution functions or cumulative age distributions CADs are the most straightforward way to visualise the probability distribution of multiple dates. Suppose that we have a set of n dates t_i. The the CAD is a step function that sets out the rank order of the dates against their numerical value:
CAD(t) = ∑_i 1(t<t_i)/n
where 1(\ast) = 1 if \ast is true and 1(\ast) = 0 if \ast is false. CADs have two desirable properties (Vermeesch, 2007). First, they do not require any pre-treatment or smoothing of the data. This is not the case for histograms or kernel density estimates. Second, it is easy to superimpose several CADs on the same plot. This facilitates the intercomparison of multiple samples. The interpretation of CADs is straightforward but not very intuitive. The prominence of individual age components is proportional to the steepness of the CAD. This is different from probability density estimates such as histograms, in which such components stand out as peaks.
Vermeesch, P., 2007. Quantitative geomorphology of the White Mountains (California) using detrital apatite fission track thermochronology. Journal of Geophysical Research: Earth Surface, 112(F3).
1 2 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.