radialplot  R Documentation 
Implementation of a graphical device developed by Rex Galbraith to display several estimates of the same quantity that have different standard errors. Serves as a vehicle to display finite and continuous mixture models.
radialplot(x, ...)
## Default S3 method:
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
transformation = "log",
sigdig = 2,
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
k = 0,
np = 3,
markers = NULL,
oerr = 3,
units = "",
hide = NA,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'other'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
transformation = "log",
sigdig = 2,
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
k = 0,
np = 3,
markers = NULL,
oerr = 3,
units = "",
hide = NA,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'fissiontracks'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
transformation = "arcsin",
sigdig = 2,
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'UPb'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
transformation = "log",
type = 4,
cutoff.76 = 1100,
cutoff.disc = discfilter(),
show.numbers = FALSE,
pch = 21,
sigdig = 2,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
common.Pb = 0,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'PbPb'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
common.Pb = 2,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'ArAr'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
i2i = FALSE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'KCa'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
i2i = FALSE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'ThPb'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
i2i = TRUE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'UThHe'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'ReOs'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
i2i = TRUE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'SmNd'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
i2i = TRUE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'RbSr'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
i2i = TRUE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'LuHf'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
exterr = FALSE,
i2i = TRUE,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
## S3 method for class 'ThU'
radialplot(
x,
from = NA,
to = NA,
z0 = NA,
sigdig = 2,
transformation = "log",
show.numbers = FALSE,
pch = 21,
levels = NA,
clabel = "",
bg = c("yellow", "red"),
col = "black",
markers = NULL,
k = 0,
np = 3,
Th0i = 0,
oerr = 3,
hide = NULL,
omit = NULL,
omit.col = NA,
...
)
x 
Either an OR and object of class 
... 
additional arguments to the generic 
from 
minimum age limit of the radial scale 
to 
maximum age limit of the radial scale 
z0 
central value 
transformation 
one of either 
sigdig 
the number of significant digits of the numerical values reported in the title of the graphical output. 
show.numbers 
boolean flag ( 
pch 
plot character (default is a filled circle) 
levels 
a vector with additional values to be displayed as different background colours of the plot symbols. 
clabel 
label of the colour legend 
bg 
Fill colour for the plot symbols. This can either be a
single colour or multiple colours to form a colour ramp (to be
used if a single colour: multiple colours: a colour palette: a reversed palette: for plot symbols, set 
col 
text colour to be used if 
k 
number of peaks to fit using the finite mixture models of
Galbraith and Laslett (1993). Setting 
np 
number of parameters for the minimum age model. Must be either 3 or 4. 
markers 
vector of ages of radial marker lines to add to the plot. 
oerr 
indicates whether the analytical uncertainties of the output are reported in the plot title as:

units 
measurement units to be displayed in the legend. 
hide 
vector with indices of aliquots that should be removed from the radial plot. 
omit 
vector with indices of aliquots that should be plotted but omitted from the central age calculation or mixture models. 
omit.col 
colour that should be used for the omitted aliquots. 
exterr 
include the external sources of uncertainty into the error propagation for the central age and mixture models? 
type 
scalar indicating whether to plot the

cutoff.76 
the age (in Ma) below which the

cutoff.disc 
discordance cutoff filter. This is an object of
class 
common.Pb 
common lead correction:

i2i 
‘isochron to intercept’: calculates the initial
(aka ‘inherited’, ‘excess’, or ‘common’) Note that choosing this option introduces a degree of circularity in the central age calculation. In this case the radial_plot plot just serves as a way to visualise the residuals of the data around the isochron, and one should be careful not to overinterpret the numerical output. 
Th0i 
initial

The radial plot (Galbraith, 1988, 1990) is a graphical device that
was specifically designed to display heteroscedastic data, and is
constructed as follows. Consider a set of dates
\{t_1,...,t_i,...,t_n\}
and uncertainties
\{s[t_1],...,s[t_i],...,s[t_n]\}
. Define z_i = z[t_i]
to be a transformation of t_i
(e.g., z_i = log[t_i]
),
and let s[z_i]
be its propagated analytical uncertainty
(i.e., s[z_i] = s[t_i]/t_i
in the case of a logarithmic
transformation). Create a scatter plot of (x_i,y_i)
values,
where x_i = 1/s[z_i]
and y_i = (z_iz_\circ)/s[z_i]
,
where z_\circ
is some reference value such as the mean. The
slope of a line connecting the origin of this scatter plot with any
of the (x_i,y_i)
s is proportional to z_i
and, hence,
the date t_i
.
These dates can be more easily visualised by drawing a radial scale at some convenient distance from the origin and annotating it with labelled ticks at the appropriate angles. While the angular position of each data point represents the date, its horizontal distance from the origin is proportional to the precision. Imprecise measurements plot on the left hand side of the radial plot, whereas precise age determinations are found further towards the right. Thus, radial plots allow the observer to assess both the magnitude and the precision of quantitative data in one glance.
does not produce any numerical output, but does report the central age and the results of any mixture modelling in the title. An asterisk is added to the plot title if the initial daughter correction is based on an isochron regression, to highlight the circularity of using an isochron to compute a central age, and to indicate that the reported uncertainties do not include the uncertainty of the initial daughter correction. This is because this uncertainty is neither purely random nor purely systematic.
Galbraith, R.F., 1988. Graphical display of estimates having differing standard errors. Technometrics, 30(3), pp.271281.
Galbraith, R.F., 1990. The radial plot: graphical assessment of spread in ages. International Journal of Radiation Applications and Instrumentation. Part D. Nuclear Tracks and Radiation Measurements, 17(3), pp.207214.
Galbraith, R.F. and Laslett, G.M., 1993. Statistical models for mixed fission track ages. Nuclear Tracks and Radiation Measurements, 21(4), pp.459470.
peakfit
, central
attach(examples)
radialplot(FT1)
dev.new()
radialplot(LudwigMixture,k='min')
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