predict.stAirPol.model: predict.stAirPol.model

In maxikellerbauer/stAirPol: Spatio-temporal Modelling of Air Pollution Data

Description

predict.stAirPol.model

Usage

## S3 method for class 'stAirPol.model'
predict(spT.model, newdata, training_set = NULL, ...)

Arguments

spT.model	a model as returned by fit_sp_model
newdata	a dataset with informations of the covariable
training_set	an object generated by get_test_and_training_set, if those an object is delivered, the newdata argument will reduced to the in training_set specified test sensors.
...	additional arguments

Value

the newdata with added columns of the prediction calculations

Examples

data("mini_dataset")
mini_dataset <- clean_model_data(mini_dataset)
formula = value ~ humi + temp + rainhist + windhist +
  trafficvol + log(sensor_age)
training_set <- get_test_and_training_set(mini_dataset, sampel_size = 0.75,
                                          random.seed = 220292)
model.gp <- fit_sp_model(data = mini_dataset, formula = formula,
                         model = 'GP', training_set = training_set)
pred.gp <- predict(model.gp, mini_dataset, training_set)

maxikellerbauer/stAirPol documentation built on May 3, 2019, 3:16 p.m.