Runs a module — run_module • osem

Runs a module in two different ways depending on whether the module is endogenously modelled or endogenous by identity/definition.

Usage

run_module(
  module,
  data,
  classification,
  use_logs = c("both", "y", "x"),
  trend = TRUE,
  ardl_or_ecm = "ardl",
  max.ar = 4,
  max.dl = 2,
  saturation = c("IIS", "SIS"),
  saturation.tpval = 0.01,
  max.block.size = 20,
  gets_selection = TRUE,
  selection.tpval = 0.01,
  opts_df,
  keep,
  pretest_steps,
  quiet
)

Arguments

module: A row of the specification table.
data: A tibble or data.frame containing the full data for the OSEM model.
classification: A data.frame with two columns: 'var' stores the Eurostat variable code and 'class' the classification code (one of "n", "d", or "x") reflecting whether the variable is endogenous by modelling, endogenous by identity/definition, or exogenous. As returned by classify_variables.
use_logs: To decide whether to log any variables. Must be one of 'both', 'y', 'x', or 'none'. Default is 'both'.
trend: Logical. Should a trend be added? Default is TRUE.
ardl_or_ecm: Either 'ardl' or 'ecm' to determine whether to estimate the model as an Autoregressive Distributed Lag Function (ardl) or as an Equilibrium Correction Model (ecm).
max.ar: Integer. The maximum number of lags to use for the AR terms. as well as for the independent variables.
max.dl: Integer. The maximum number of lags to use for the independent variables (the distributed lags).
saturation: Carry out Indicator Saturation using the 'isat' function in the 'gets' package. Needs a character vector or string. Default is 'c("IIS","SIS")' to carry out Impulse Indicator Saturation and Step Indicator Saturation. Other possible values are 'NULL' to disable or 'TIS' or Trend Indicator Saturation. When disabled, estimation will be carried out using the 'arx' function from the 'gets' package.
saturation.tpval: The target p-value of the saturation methods (e.g. SIS and IIS, see the 'isat' function in the 'gets' package). Default is 0.01.
max.block.size: Integer. Maximum size of block of variables to be selected over, default = 20.
gets_selection: Logical. Whether general-to-specific selection using the 'getsm' function from the 'gets' package should be done on the final saturation model. Default is TRUE.
selection.tpval: Numeric. The target p-value of the model selection methods (i.e. general-to-specific modelling, see the 'getsm' function in the 'gets' package). Default is 0.01.
opts_df: Internal object containing detailed options and information on individual modules.
keep: Character. A string that will be used as regex (in grepl()) when selection is carried out. This argument therefore requires gets_selection = TRUE. Variables that match this character will not be selected over (see getsm for details).
pretest_steps: Logical. Default is FALSE. This argument controls whether isat should first be run for SIS in isolation before other saturation methods are added (IIS, TIS). This can lead to better results if there are many IIS identified at the end of the estimation sample/forecast origin. If TRUE then isat is first carried out just for SIS (if activated using 'sis = TRUE'), then the SIS breaks are pre-entered to another isat estimation but not selected over. After both isat runs, a union model selection is done using gets.
quiet: Logical. Should messages about the forecast procedure be suppressed?

Value

Returns a list with two named elements.

model: For endogenously modeled modules (type == "n"), an object of class isat or arx. For identity/definition modules (type == "d"), NULL.
data: The data (including transformations) that was used to estimate the model and the fitted values of the dependent variable.