Create a measurementTable from concatenated ensembles

This "shuffles" together two *independent* ensemble datasets, making no assumptions about stratigraphic order, but assuming that each dataset is representing the same phenomenon.

createConcatenatedEnsembleMeasurementTable(
  age.ens.1,
  paleo.data.1,
  age.ens.2,
  paleo.data.2,
  n.ens = 1000
)

Arguments

age.ens.1

Age ensemble list for the first dataset

paleo.data.1

Paleo data list for the first dataset (ensembles optional)

age.ens.2

Age ensemble list for the second dataset

paleo.data.2

Paleo data list for the second dataset (ensembles optional)

n.ens

How many ensemble members?

Value

A measurement table object

See also

Other LiPD manipulation: createModel(), createMultiModelEnsemble(), createSummaryTableFromEnsembleTable(), createTSid(), estimateUncertaintyFromRange(), getVariableIndex(), mapAgeEnsembleToPaleoData(), pullTsVariable(), selectData()

Examples

if (FALSE) {
library(lipdR)
library(geoChronR)
library(magrittr)

L1 <- readLipd("~/Downloads/ANS1.Kjellman.2019.lpd")
L2 <- readLipd("~/Downloads/ANP3.Kjellman.2019.lpd")


#composite two independent records
L1 <- mapAgeEnsembleToPaleoData(L1,paleo.meas.table.num = 1,age.var = "ageEnsemble")

age.ens.1 <- selectData(L1,"ageEnsemble",meas.table.num = 1)
paleo.data.1 <- selectData(L1,"C28d2H",,meas.table.num = 1)

L2 <- mapAgeEnsembleToPaleoData(L2,paleo.meas.table.num = 1,age.var = "ageEnsemble")
age.ens.2 <- selectData(L2,"ageEnsemble",meas.table.num = 1)
paleo.data.2 <- selectData(L2,"C28d2H",,meas.table.num = 1)
cmt <- createConcatenatedEnsembleMeasurementTable(age.ens.1,paleo.data.1,age.ens.2,paleo.data.2)
plotTimeseriesEnsRibbons(X = cmt$ageEnsemble,Y = cmt$C28d2HComposite) %>%
plotTimeseriesEnsLines(X = cmt$ageEnsemble,Y = cmt$C28d2HComposite,n.ens.plot = 5,color = "red")
}