
## S3 method for class 'wa':
predict(object, newdata,
CV = c("none", "LOO", "bootstrap", "nfold"),
verbose = FALSE, n.boot = 100, nfold = 5, ...)
"wa"
, usually the result of a
call to wa
"LOO"
), bootstrap ("bootstrap"
) and $k$-fold
("nfold"
) CV are currently available."predict.wa"
, a list with the following
components:pred
and rmsep
containing the predicted values and the sample specific errors if
available.pred
and rmsep
containing the predicted values for the training set samples and the
sample specific errors if available.CV = "bootstrap"
and
CV = "nfold"
produce sample specific errors.wa
, predict.mat
,
performance
, reconPlot
.## Imbrie and Kipp
data(ImbrieKipp)
data(SumSST)
ik.wa <- wa(SumSST ~ ., data = ImbrieKipp, tol.dw = TRUE,
min.tol = 2, small.tol = "min")
ik.wa
## load V12.122 core data
data(V12.122)
V12.122 <- V12.122 / 100
## predict summer sea-surface temperature for V12.122 core
set.seed(2)
v12.pred <- predict(ik.wa, V12.122, CV = "bootstrap", n.boot = 100)
## draw the fitted reconstruction
reconPlot(v12.pred, use.labels = TRUE, display = "bars")
## extract the model performance stats
performance(v12.pred)
Run the code above in your browser using DataLab