fit_its_model — fit_its_model • multipleITScontrol

Fits an interrupted time series model using the nlme package, defaulting to an autocorrelation-moving average correlation structure of order (p, q)

Usage

fit_its_model(
  transformed_data,
  impact_model,
  num_interventions,
  method = "REML",
  grid_search = TRUE,
  p = NULL,
  q = NULL,
  return_grid_search = FALSE,
  ...
)

Arguments

transformed_data: Am unmodified data frame created from `transform_data()`.
impact_model: The hypothesized impact model from interventions. Available options are 'level', 'slope', or 'levelslope'.
num_interventions: The number of interventions in your transformed data. Should be the vector length of `intervention_dates` passed in `transform_data()`.
method: The estimation method for `nlme::gls()`, either "REML" (default) or "ML".
grid_search: logical for whether to perform a grid search for determining lag parameters (p = AR, q = MA). By default, a grid up to values of 5 for each parameter is searched.
p: The order of the autoregressive component. Defaults to `NULL`. If `grid_search is enabled`, this argument is ignored.
q: The order of the moving average component. Defaults to `NULL`. If `grid_search is enabled`, this argument is ignored.
return_grid_search: Logical flag returns the result of the grid search instead of the model. 'FALSE' by default.
...: Additional arguments passed to `nlme::gls()`.

Value

A `gls` object of the fitted model.