chorussell.bs: Bootstrap procedure for the 'chorussell' procedure
In conroylau/lpinfer: An R Package for Inference in Linear Programs

chorussell.bs

R Documentation

Bootstrap procedure for the `chorussell` procedure

Description

This function carries out the bootstrap procedure of the chorussell procedure. This function supports parallel programming via the future_map function.

Usage

chorussell.bs(
  data,
  lpmodel,
  beta.tgt,
  R,
  maxR,
  kappa,
  norm,
  n,
  estimate,
  solver,
  progress
)

Arguments

`data`	An `data frame` or a `matrix`.
`lpmodel`	The `lpmodel` object.
`beta.tgt`	The value to be tested.
`R`	The number of bootstrap replications.
`maxR`	The maximum number of bootstrap replications to be considered in case there are some errors.
`kappa`	The tuning parameter used in the second step of the two-step procedure for obtaining the bounds subject to the shape constraints. It can be any nonnegative number or a vector of nonnegative numbers.
`norm`	The norm used in the optimization problem. It can be either a 1-norm or a 2-norm. See the details section of `estbounds` for a list of accepted strings.
`n`	The sample size. This is only required if `data` is omitted in the input.
`estimate`	A boolean variable to indicate whether the bounds should be estimated or not.
`solver`	The name of the linear and quadratic programming solver that is used to obtain the solution to linear and quadratic programs. The solvers supported by this package are `cplexAPI`, `gurobi`, `limSolve` and `Rcplex`.
`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.

Value

Returns a list of output that are obtained from the Cho-Russell procedure:

`ub.bs`	The list of upper bounds from bootstrap data.
`lb.bs`	The list of lower bounds from bootstrap data.
`df.error`	A table showing the id of the bootstrap replication(s) with error(s) and the corresponding error message(s).
`error.list`	A list of error messages.
`R.eval`	The number of bootstrap replications that have been conducted.
`R.succ`	The number of successful bootstrap replications.