par_bs_ci: Parametric bootstrapped confidence intervals to control RCC

Description Usage Arguments Value Examples

View source: R/par_bs_ci.R

Description

This function implements the parametric bootstrap (see Section 2.3 of the referenced paper). The user supplies point estimates, standard errors and optionally, a ranking function.

Usage

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par_bs_ci(beta, se = rep(1, length(beta)), rank.func = NULL, theta = beta,
  level = 0.9, n.rep = 1000, use.abs = TRUE, ...)

Arguments

beta

Parameter estimates

se

Estimated standard error of beta. Defaults to 1.

rank.func

A function that takes as first argument the t-statistics beta/se and returns a list with items order and rank. See rcc:::basic_rank for an example. If NULL, the basic_rank function will be used which ranks based on the size of the test statistics.

theta

Possibly shrunken estimates of E[beta]. Defaults to beta.

level

Confidence level

n.rep

Number of bootstrap replications

use.abs

Base the rank on abs(beta) rather than beta

...

Additional parameters to pass to rank.func

Value

A data frame giving original estimates and standard errors, confidence intervals, debiased point estimates, and rank for each parameter.

Examples

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#generate 100 fake parameter estimates
theta <- c(rep(0, 90), rnorm(n=10)) #vector of means
beta <- rnorm(n=100, mean=theta, sd=1)
cis <- par_bs_ci(beta=beta, n.rep=500) #calculate parametric bootstrap confidence intervals
head(cis)

rcc documentation built on May 29, 2017, 9:12 a.m.