Description Usage Arguments Value
Predict using spLearner at new locations
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## S3 method for class 'spLearner'
predict(
object,
predictionLocations,
model.error = TRUE,
error.type = c("forestError", "weighted.sd", "quantreg", "interval")[1],
t.prob = 1/3,
w,
quantiles = c((1 - 0.682)/2, 1 - (1 - 0.682)/2),
n.cores = parallel::detectCores(),
what = c("mspe", "bias", "interval"),
...
)
|
object |
of type |
predictionLocations |
|
model.error |
Logical specify if prediction errors should be derived. |
error.type |
Specify how should be the prediction error be derived. |
t.prob |
Threshold probability for significant learners; only applyies for meta-learners based on lm model. |
w |
optional weights vector. |
quantiles |
Lower and upper quantiles for quantreg forest (0.159 and 0.841 for 1 standard deviation). |
n.cores |
Number of cores to use (for parallel computation in ranger). |
what |
A vector of characters indicating what estimates are desired for the quantForestError. |
... |
optional parameters. |
Object of class SpatialPixelsDataFrame
with predictions and model error.
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