chorussell.lp: Computes the (1-alpha)-confidence interval in the...

View source: R/chorussell.R

chorussell.lpR Documentation

Computes the (1-α)-confidence interval in the chorussell procedure

Description

This function computes the (1-α)-confidence interval in the chorussell procedure by solving the optimization problem.

Usage

chorussell.lp(
  lb.can1,
  lb.can2,
  ub.can1,
  ub.can2,
  n,
  R,
  alpha,
  ub,
  lb,
  logical.ub,
  logical.lb,
  remove.const,
  ci,
  kappa,
  k = 0,
  progress,
  df.lb,
  df.ub
)

Arguments

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.

alpha

The significance level. This can be a vector.

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.

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.

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.

k

Iteration number.

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

Returns the following list of objects:

bd

A vector that represents the (1-α)-confidence interval.

unique

An indicator variable of whether the solution is unique.


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