rmw_predict_nested_sets: Function to make predictions from a random forest models...

In rmweather: Tools to Conduct Meteorological Normalisation and Counterfactual Modelling for Air Quality Data

Function to make predictions from a random forest models using a nested tibble.

Description

Function to make predictions from a random forest models using a nested tibble.

Usage

rmw_predict_nested_sets(
  df_nest,
  se = FALSE,
  n_cores = NULL,
  keep_vectors = FALSE,
  model_errors = FALSE,
  as_long = TRUE,
  partial = FALSE,
  verbose = FALSE,
  progress = FALSE
)

Arguments

df_nest	Nested tibble created by rmw_model_nested_sets.
se	Should the standard error of the predictions be calculated?
n_cores	Number of CPU cores to use for the model calculations.
keep_vectors	Should the prediction vectors be kept in the return? This is usually not needed because these vectors have been added to the observations variable.
model_errors	Should model error statistics between the observed and predicted values be calculated and returned?
as_long	For when model_errors is TRUE, should the model error unit be returned in "long format"?
partial	Should the model's partial dependencies also be calculated? This will increase the execution time of the function.
verbose	Should the function give messages?
progress	Should a progress bar be displayed?

Value

Nested tibble.

Author(s)

Stuart K. Grange

See Also

rmw_nest_for_modelling, rmw_model_nested_sets, rmw_predict, rmw_calculate_model_errors, rmw_partial_dependencies

rmweather documentation built on June 22, 2024, 9:33 a.m.