bury | R Documentation |
Computes the age-depth curve from the output of the MCMC algorithm and the known depth of each dated samples.
bury(object, depth, ...)
## S4 method for signature 'EventsMCMC,numeric'
bury(object, depth)
## S4 method for signature 'AgeDepthModel'
predict(object, newdata)
## S4 method for signature 'AgeDepthModel,missing'
plot(
x,
level = 0.95,
calendar = getOption("ArchaeoPhases.calendar"),
main = NULL,
sub = NULL,
ann = graphics::par("ann"),
axes = TRUE,
frame.plot = axes,
panel.first = NULL,
panel.last = NULL,
...
)
object |
An |
depth |
A |
... |
Other graphical parameters may also be passed as
arguments to this function, particularly, |
newdata |
A |
x |
An |
level |
A length-one |
calendar |
A |
main |
A |
sub |
A |
ann |
A |
axes |
A |
frame.plot |
A |
panel.first |
An an |
panel.last |
An |
We assume it exists a function f
relating the age and the depth
age = f(depth)
. We estimate the function using local regression
(also called local polynomial regression): f = loess(age ~ depth)
.
This estimated function f
depends on the unknown dates. However,
from the posterior distribution of the age/date sequence, we can evaluate
the posterior distribution of the age function for each desired depth.
bury()
returns an AgeDepthModel
object.
predict()
returns an EventsMCMC
object.
plot()
is called it for its side-effects: it results in a graphic being
displayed (invisibly returns x
).
A. Philippe
Jha, D. K., Sanyal, P. & Philippe, A. (2020). Multi-Proxy Evidence of Late Quaternary Climate and Vegetational History of North-Central India: Implication for the Paleolithic to Neolithic Phases. Quaternary Science Reviews, 229: 106121. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.quascirev.2019.106121")}.
Ghosh, S., Sanyal, P., Roy, S., Bhushan, R., Sati, S. P., Philippe, A. & Juyal, N. (2020). Early Holocene Indian Summer Monsoon and Its Impact on Vegetation in the Central Himalaya: Insight from dD and d13C Values of Leaf Wax Lipid. The Holocene, 30(7): 1063-1074. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/0959683620908639")}.
Other age-depth modeling tools:
interpolate()
## Coerce to MCMC
eve <- matrix(rnorm(6000, (1:6)^2), ncol = 6, byrow = TRUE)
eve <- as_events(eve, calendar = CE())
## Compute an age-depth curve
age <- bury(eve, depth = 1:6)
plot(age)
## Predict new values
new <- predict(age, newdata = 1.5:5.5)
summary(new)
plot(eve)
plot(new)
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