simulateBam | R Documentation |
Generate an ensemble of possible age corrected data:See www.clim-past-discuss.net/9/6077/2013/ for a detailed description of the model. The time series in X are automatically flipped to range from most recent to oldest measurements when the input t is given in increasing order.
simulateBam(X, t, model = NULL, ageEnsOut = FALSE)
X |
data (vector or matrix n*p) |
t |
chronology for data X (n*1) |
model |
a list that describes the model to use in BAM
|
ageEnsOut |
TRUE or FALSE - return the ageEnsemble |
res a list with
res$Xc: realizations of age-perturbed data matrix of size tn*p*ns (could be 2 or 3d)
res$tc: new chronology tn*1
res$tmc: corresponding ensemble of time-correction matrices (tn*p*ns) to map realizations in Xp back to the original data X (2=insert nan, 0=remove double band) (2 or 3d) where tn is the chronology length = n (default), shortest sample or longest sample depending on the chosen resizing option.
res$ageEnsemble (optional): Returnd the full age ensemble if desired.
Maud Comboul
Other BAM:
bamCorrect()
,
runBam()
## Not run:
res <- simulateBam(X,t)
#will generate an ensemble of 1000 age models randomly following
#a Poisson process with rate parameter theta=0.05 used to perturb data X
res <- simulateBam(X,t,model)
#will perturb data X with the model specified in
#the model structure
## End(Not run)
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