normalise_for_meteorology: Function to normalise a concentration variable based on...

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

Description

Function to normalise a concentration variable based on "average" meteorological conditions.

Usage

normalise_for_meteorology(list_model, df, variables, n = 100,
  replace = FALSE, output = NA)

Arguments

list_model	A normalweatherr_model model object, created with calculate_model.
df	Data frame to use for prediction. Created with split_input_data.
variables	Variables to include in the randomly sample.
n	Number of times to sample df.
replace	Should variables be sampled with replacement?
output	File name to export the model object as an .rds file. If not used, the model will not be exported to disc. Directories will be created if necessary.

Value

Data frame.

Author(s)

Stuart K. Grange

See Also

split_input_data, calculate_model

Examples

## Not run: 

# Create a meteorologically normalised time series
data_normalised <- normalise_for_meteorology(
  list_model = list_input_data$model, 
  df = data_swiss_daily, 
  variables = setdiff(variables, "date_unix"),
  n = 1000,
  output = NA
)


## End(Not run)

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