sampleEnsembleThenBinTs | R Documentation |
sampleEnsembleThenBinTs
sampleEnsembleThenBinTs(
ts,
binvec,
ageVar = "age",
uncVar = "paleoData_uncertainty1sd",
defaultUnc = 1.5,
ar = sqrt(0.5),
bamModel = list(ns = 1, name = "bernoulli", param = 0.05),
spread = TRUE,
spreadBy = abs(mean(diff(binvec)))/10,
spreadMax = as.numeric(stats::quantile(abs(diff(thisAge)), probs = 0.75, na.rm = TRUE)),
gaussianizeInput = FALSE,
alignInterpDirection = TRUE,
scope = "climate"
)
ts |
a lipd_ts object |
binvec |
vector of time boundaries over which to bin |
ageVar |
specify the name the time variable (typically 'age' or 'year') |
uncVar |
specify the name the uncertainty variable |
defaultUnc |
a uncertainty to use if uncVar is NULL (default = 1.5 paleoData_units) |
ar |
Autocorrelation coefficient to use for modelling uncertainty on paleoData, what fraction of the uncertainties are autocorrelated? (default = sqrt(0.5); or 50 percent autocorrelated uncertainty) |
bamModel |
a list that describes the model to use in BAM (default = list(ns = 1, name = "bernoulli", param = 0.05)) |
spread |
should values be interpolated between bins? (TRUE/FALSE) |
spreadBy |
if newAge is not supplied, what is the desired resolution of the spread values? If NA, the minimum age gap divided by 5 will be used |
spreadMax |
a limit to how many years a value can be interpolated across (given in years). If NA, no limit is imposed. |
gaussianizeInput |
Force values to gaussian distribution before analysis (TRUE/FALSE) |
alignInterpDirection |
multiply values by -1 if scope_interpDirection == negative (TRUE/FALSE) |
scope |
the scope of the project (typically "climate" (default) or "isotope") |
numeric vector of values of equal length to binvec
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