rmw_normalise_nested_sets: Function to normalise a variable for "average" meteorological...

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

Function to normalise a variable for "average" meteorological conditions in a nested tibble.

Description

Function to normalise a variable for "average" meteorological conditions in a nested tibble.

Usage

rmw_normalise_nested_sets(
  df_nest,
  variables = NA,
  n_samples = 10,
  replace = TRUE,
  se = FALSE,
  aggregate = TRUE,
  keep_samples = FALSE,
  n_cores = NA,
  verbose = FALSE,
  progress = FALSE
)

Arguments

df_nest	Nested tibble created by rmw_model_nested_sets.
variables	Variables to randomly sample. Default is all variables used for training the model with the exception of date_unix, the trend term.
n_samples	Number of times to sample df and then predict?
replace	Should variables be sampled with replacement?
se	Should the standard error of the predictions be calculated too? The standard error method is the "infinitesimal jackknife for bagging" and will slow down the predictions significantly.
aggregate	Should all the n_samples predictions be aggregated?
keep_samples	When aggregate is FALSE, should the sampled/shuffled observations be kept?
n_cores	Number of CPU cores to use for the model predictions. Default is system's total minus one.
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_model_nested_sets, rmw_normalise.

skgrange/rmweather documentation built on May 10, 2024, 8:49 a.m.