R/choosePositions.BchronologyRun.R
choosePositions.RdThis function finds, for a given current chronology, created via
Bchronology, which positions (depths) to date next
If N = 1 it just finds the position with the biggest uncertainty
If N>1 it puts a date at the N = 1 position and re-runs
Bchronology with the extra psuedo date. It uses the
unCalibrate function with the un-calibrated age estimated
at the median of the chronology and the sd as specified via the
newSds argument. Other arguments specify the new thicknesses,
calibration curves, and outlier probabilities for newly inserted psuedo-dates.
choosePositions(
bchrRun,
N = 1,
newSds = 30,
newThicknesses = 0,
positions = bchrRun$predictPositions,
newCalCurve = "intcal20",
newOutlierProb = 0.05,
level = 0.5,
plot = TRUE,
count = 1,
linesAt = NULL
)A run of the current chronology as output from Bchronology
The number of new positions required
The new standard deviations of the psuedo-added dates
The new thicknesses of the psuedo-added dates
The positions allowed to estimate the new positions to date. Defaults to the value of predictPositions from the
Bchronology run
The new calibration curve of the psuedo-added dates
The new outlier probabilities of the psuedo-added dates
The confidence level required for minimising the uncertainty. Defaults to 50%. (Note: this will be estimated more robustly than the 95% level)
Whether to plot the chronologies as they are produced
Counter function (not for use other than by the function itself)
Horizontal line positions (not for use other than by the function itself)
Some plots and the positions to date next
Bchronology for the main function to create chronologies, unCalibrate for the ability to invert calendar dates for a given calibration curve.
# \donttest{
data(Glendalough)
GlenOut <- Bchronology(
ages = Glendalough$ages,
ageSds = Glendalough$ageSds,
calCurves = Glendalough$calCurves,
positions = Glendalough$position,
positionThicknesses = Glendalough$thickness,
ids = Glendalough$id,
predictPositions = seq(0, 1500, by = 10)
)
#> Running Bchronology...
#>
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#> Run completed!
# Find out which two positions (depths) to date if we have room for two more dates
# Here going to choose 3 new positions to date
newPositions <- choosePositions(GlenOut, N = 3)
#>
#> Round 1
#> Position with largest uncertainty at 50% level is 830
#>
|
|================================================================| 100%
#> Calibrating with new age 5898 with sd 30 at position 830
#> Running Bchronology...
#>
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#> Run completed!
#>
#>
#> Round 2
#> Next position with largest uncertainty at 50% level is 630
#>
|
|================================================================| 100%
#> Calibrating with new age 4081 with sd 30 at position 630
#> Running Bchronology...
#>
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#> Run completed!
#>
#>
#> Round 3
#> Next position with largest uncertainty at 50% level is 1000
print(newPositions)
#> [1] 830 630 1000
# Suppose you are only interested in dating the new depths at 500, 600, or 700 cm
newPositions2 <- choosePositions(GlenOut,
N = 2,
positions = seq(500, 700, by = 10)
)
#>
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#> Round 1
#> Position with largest uncertainty at 50% level is 690
#>
|
|================================================================| 100%
#> Calibrating with new age 4464 with sd 30 at position 690
#> Running Bchronology...
#>
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|===================================================== | 89%
|
|====================================================== | 89%
|
|====================================================== | 90%
|
|====================================================== | 91%
|
|======================================================= | 91%
|
|======================================================= | 92%
|
|======================================================== | 93%
|
|======================================================== | 94%
|
|========================================================= | 94%
|
|========================================================= | 95%
|
|========================================================= | 96%
|
|========================================================== | 96%
|
|========================================================== | 97%
|
|=========================================================== | 98%
|
|=========================================================== | 99%
|
|============================================================| 99%
|
|============================================================| 100%
#> Run completed!
#>
#>
#> Round 2
#> Next position with largest uncertainty at 50% level is 530
print(newPositions2)
#> [1] 690 530
# }