normalise_variables: Function to normalise for meteorology for many variables.

In skgrange/normalweatherr: An R package to conduct meteorological/weather normalisation on air quality data

Description

Function to normalise for meteorology for many variables.

Usage

normalise_variables(df, variables, variables_explanatory, model = "rf",
  ntree = 10, mtry = 3, nodesize = 3, n_predict = 10, verbose = TRUE)

Arguments

df	Data frame containing a date variable.
variables	Variables in df to normalise for meteorology.
variables_explanatory	Variables to include in the model, i.e. the predictors.
model	Model type to use. Default is "rf" for random forest. See calculate_model for details.
ntree	Number of trees to grow for "rf" or "gbm" models. Default is low for testing purposes, increase for usable models.
mtry	Number of variables randomly sampled for splitting the "rf" decision tree.
nodesize	Minimum size of terminal nodes for the "rf" model.
n_predict	Number of times to sample input data and predict using the model.
verbose	Should the function give messages?

Value

Named list with split input data, model performance data, and normalised data.

Author(s)

Stuart K. Grange

See Also

add_date_variables, split_input_data, calculate_model, normalise_for_meteorology

skgrange/normalweatherr documentation built on May 23, 2019, 9:34 a.m.