gauge_avar: Asymptotic variance of gauge
In robust2sls: Outlier Robust Two-Stage Least Squares Inference and Testing

gauge_avar

R Documentation

Asymptotic variance of gauge

gauge_avar calculates the asymptotic variance of the gauge for a given iteration using a given set of parameters (true or estimated).

gauge_avar(
  ref_dist = c("normal"),
  sign_level,
  initial_est = c("robustified", "saturated", "iis"),
  iteration,
  parameters,
  split
)

`ref_dist`	A character vector that specifies the reference distribution against which observations are classified as outliers. `"normal"` refers to the normal distribution.
`sign_level`	A numeric value between 0 and 1 that determines the cutoff in the reference distribution against which observations are judged as outliers or not.
`initial_est`	A character vector that specifies the initial estimator for the outlier detection algorithm. `"robustified"` means that the full sample 2SLS is used as initial estimator. `"saturated"` splits the sample into two parts and estimates a 2SLS on each subsample. The coefficients of one subsample are used to calculate residuals and determine outliers in the other subsample. `"iis"` applies impulse indicator saturation (IIS) as implemented in `ivisat`.
`iteration`	An integer >= 0 or character `"convergence"` representing the iteration for which the outliers are calculated. Uses the fixed point value if set to `"convergence"`.
`parameters`	A list created by generate_param or estimate_param_null that stores the parameters (true or estimated). `NULL` permitted if `ref_dist == "normal"`.
`split`	A numeric value strictly between 0 and 1 that determines in which proportions the sample will be split. Can be `NULL` if `initial_est == "robustified"`.