landmap (version 0.0.13)

predict.spLearner: Predict using spLearner at new locations

Description

Predict using spLearner at new locations

Usage

# S3 method for 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"),
  ...
)

Arguments

object

of type spLearner.

predictionLocations

SpatialPixelsDataFrame with values of all features.

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.

Value

Object of class SpatialPixelsDataFrame with predictions and model error.