Define a discordance cutoff to filter U--Pb data.
discfilter(option = 0, before = TRUE, cutoff)a list with the input parameters. Default values for
cutoff are
c(-48,140) if option=='t';
c(-5,15) if option=='r';
c(-0.36,0.96) if option=='sk';
c(-1.6,4.7) if option=='a'; and
c(-2,5.8) if option=='c'.
one of five options:
0: do not apply a discordance filter
1 or 't': the absolute age difference (Ma) between
the \(^{206}\)Pb/\(^{238}\)U and \(^{207}\)Pb/\(^{206}\)Pb
ages.
2 or 'r': the relative age difference (%) between the
\(^{206}\)Pb/\(^{238}\)U and \(^{207}\)Pb/\(^{206}\)Pb ages.
3 or 'sk': percentage of common Pb measured along a
mixing line connecting the measured composition and the
Stacey-Kramers mantle composition in Tera-Wasserburg space.
4 or 'a': logratio distance (%) measured along a
perpendicular line connecting Tera-Wasserburg concordia and the
measured composition.
5 or 'c': logratio distance (%) measured along a
line connecting the measured composition and the corresponding
single grain concordia age composition.
Further details in Vermeesch (2021).
logical flag indicating whether the discordance
filter should be applied before (TRUE) or after
(FALSE) the common-Pb correction.
a two-element vector with the minimum (negative) and
maximum (positive) allowed discordance. Default values vary
between the different options. To view them, enter
discfilter(option) at the R command line.
The most reliable U--Pb age constraints are obtained from (zircon) grains whose \(^{206}\)Pb/\(^{238}\)U and \(^{207}\)Pb/\(^{206}\)Pb ages are statistically indistinguishable from each other. U--Pb compositions that fulfil this requirements are called `concordant'. Those that violate it are called `discordant'. The discordance of the \(^{206}\)Pb/\(^{238}\)U and \(^{207}\)Pb/\(^{206}\)Pb systems can be defined in five different ways. By setting a cutoff for any of these criteria, U--Pb data can be filtered for data quality.
Vermeesch (2021) ``On the treatment of discordant data in detrital zircon U--Pb geochronology'', Geochronology.
cad, kde,
radialplot
dscf <- discfilter(option='c',before=TRUE,cutoff=c(-1,1))
weightedmean(x=examples$UPb,exterr=FALSE,sigdig=2,
cutoff.disc=dscf,common.Pb=3)
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