coreInfluence {Bchron} | R Documentation |
This function takes as input two Bchronology
runs and compares the uncertainty intervals. It does this by
computing the mean uncertainty across the core (type = 'mean'
) at a specified percentile level (e.g. 95%) and
subsequently reporting the reduction/increase in uncertainty between the two runs. Both cores must
have the same set of depths/positions at regular intervals.
coreInfluence(
bchrRun1,
bchrRun2,
percentile = 0.95,
type = c("plot", "summary", "max"),
ageTolerance = 500,
...
)
bchrRun1 |
The output of a run of the |
bchrRun2 |
The output of another run of the |
percentile |
The value of the percentile to compare the uncertainties. Default is 95% |
type |
if |
ageTolerance |
A value in years for which to report the positions at which the reduction in uncertainty exceeds this value. |
... |
Additional arguments to plot |
For example, if the ageTolerance
value is 500 years, then coreInfluence
will return all of the positions at
which the uncertainty reduction is bigger than 500.
Depending on type will outputs some text and plots providing the influence values for the cores in question.
Bchronology
, choosePositions
, dateInfluence
for finding the influence of removing a single date from a core
data(Glendalough)
# Start with a run that remove two dates
GlenOut1 <- Bchronology(
ages = Glendalough$ages[-c(3:4)],
ageSds = Glendalough$ageSds[-c(3:4)],
calCurves = Glendalough$calCurves[-c(3:4)],
positions = Glendalough$position[-c(3:4)],
positionThicknesses = Glendalough$thickness[-c(3:4)],
ids = Glendalough$id[-c(3:4)],
predictPositions = seq(0, 1500, by = 10)
)
GlenOut2 <- 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)
)
# Now compare their influence
coreInfluence(GlenOut1,
GlenOut2,
type = c("max", "plot"),
xlab = "Age (cal years BP)",
ylab = "Depth (cm)",
main = "Chronology difference at 95% for
Glendalough removing two dates",
las = 1
)