chorussell.eval: Computes the required object in the 'chorussell' procedure

In conroylau/lpinfer: An R Package for Inference in Linear Programs

Computes the required object in the chorussell procedure

Description

This function computes the required object in the chorussell procedure. If ci is TRUE, this function returns the (1-α)-confidence interval. Otherwise, it returns the p-value.

Usage

chorussell.eval(
  beta.tgt,
  lb.can1,
  lb.can2,
  ub.can1,
  ub.can2,
  n,
  R,
  ci,
  alpha,
  tol,
  ub,
  lb,
  logical.ub,
  logical.lb,
  remove.const,
  kappa,
  progress,
  df.lb = NULL,
  df.ub = NULL
)

Arguments

beta.tgt	The value to be tested.
lb.can1	The vector of values that corresponds to √{n}≤ft(\hat{θ}^b_{\rm lb} - \hat{θ}_{\rm lb}\right).
lb.can2	The vector of values that corresponds to √{n}≤ft(\hat{θ}^b_{\rm lb} - \hat{θ}_{\rm lb} - Δ \right).
ub.can1	The vector of values that corresponds to √{n}≤ft(\hat{θ}^b_{\rm ub} - \hat{θ}_{\rm ub}\right).
ub.can2	The vector of values that corresponds to √{n}≤ft(\hat{θ}^b_{\rm ub} - \hat{θ}_{\rm ub} + Δ \right).
n	The sample size. This is only required if data is omitted in the input.
R	The number of bootstrap replications.
ci	A boolean variable that indicates whether a p-value or a (1-α)-confidence interval is returned. If ci is TRUE, then a confidence interval is returned. Otherwise, a p-value is returned.
alpha	The significance level. This can be a vector.
tol	The tolerance level in the bisection procedure.
ub	The sample upper bound.
lb	The sample lower bound.
logical.ub	The logical upper bound.
logical.lb	The logical lower bound.
remove.const	A boolean variable. This determine whether the constraints are to be removed.
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.
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.lb	The list of lower bounds that are obtained from the simplified program.
df.ub	The list of upper bounds that are obtained from the simplified program.

Value

Depending on ci, this function either returns the p-value or the (1-α)-confidence interval.

conroylau/lpinfer documentation built on Oct. 23, 2022, 9:21 a.m.