gauge_avar: Asymptotic variance of gauge

In robust2sls: Outlier Robust Two-Stage Least Squares Inference and Testing

Asymptotic variance of gauge

Description

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

Usage

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

Arguments

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".

Details

Initial estimator "iis" uses the asymptotic variances of "robustified" 2SLS because there is no formal theory for the multi-block search.

Value

gauge_avar returns a numeric value.

robust2sls documentation built on Jan. 11, 2023, 5:13 p.m.