fsst.beta.bs: Computing the bootstrap estimates of 'beta.obs'
In conroylau/lpinfer: An R Package for Inference in Linear Programs

fsst.beta.bs

R Documentation

Computing the bootstrap estimates of `beta.obs`

This function computes the bootstrap estimates of \hat{β}_{{\rm obs}, n}.

fsst.beta.bs(
  n,
  data,
  beta.obs.hat,
  lpmodel,
  R,
  maxR,
  progress,
  df.error,
  iseq,
  eval.count
)

`n`	The sample size. This is only required if `data` is omitted in the input.
`data`	An `data frame` or a `matrix`.
`beta.obs.hat`	The sample estimator \widehat{\bm{β}}_{\mathrm{obs}, n} based on the given information in `lpmodel` (and `data` if applicable).
`lpmodel`	An `lpmodel` object.
`R`	The number of bootstrap replications.
`maxR`	The maximum number of bootstrap replications to be considered in case there are some errors.
`progress`	The boolean variable for whether the progress bars should be displayed. If it is set as `TRUE`, the progress bars will be displayed while the code is running.
`df.error`	A table showing the id of the bootstrap replication(s) with error(s) and the corresponding error message(s).
`iseq`	The list of indices or betas to iterate over.
`eval.count`	The count for the number of times the `future_map` function has been called. If this object is zero, it means that the `future_map` function is being called for the first time in this subprocedure. Otherwise, it means that the `future_map` function has been called for more than once. This situation typically refers to the situations where there are some errors in the first time of the replications.

Returns the bootstrap estimators.

`beta.obs.bs`	A list of bootstrap estimators \{\hat{β}_{{\rm obs}, n, b}\}^B_{b=1}.
`df.error`	An updated table showing the id of the bootstrap replication(s) with error(s) and the corresponding error message(s).
`R.eval`	The number of bootstrap replications that has been conducted.
`R.succ`	The number of successful bootstrap replications.