PB.CI: Provide '(1-alpha)%' confidence interval of each coefficients
In EAinference: Estimator Augmentation and Simulation-Based Inference

Description Usage Arguments Details Value References Examples

Using samples drawn by PBsampler, computes (1-alpha)% confidence interval of each coefficient.

1 2	PB.CI(object, alpha = 0.05, method = "debias", parallel = FALSE, ncores = 2L)

`object`	bootstrap samples of class `PB` from `PBsampler`
`alpha`	significance level.
`method`	bias-correction method. Either to be "none" or "debias".
`parallel`	logical. If `TRUE`, use parallelization. Default is `FALSE`.
`ncores`	integer. The number of cores to use for parallelization.

If method = "none", PB.CI simply compute the two-sided (1-alpha) quantile of the sampled coefficients. If method = "debias", we use debiased estimator to compute confidence interval.

(1-alpha)% confidence interval of each coefficients

Zhang, C., Zhang, S. (2014), "Confidence intervals for low dimensional parameters in high dimensional linear models," Journal of the Royal Statistical Society: Series B, 76, 217–242.

Dezeure, R., Buhlmann, P., Meier, L. and Meinshausen, N. (2015), "High-Dimensional Inference: Confidence Intervals, p-values and R-Software hdi," Statistical Science, 30(4), 533-558

set.seed(1234)
n <- 40
p <- 50
Niter <-  10
X <- matrix(rnorm(n*p), n)
object <- PBsampler(X = X, PE_1 = c(1,1,rep(0,p-2)), sig2_1 = 1, lbd_1 = .5,
niter = 100, type = "lasso")
parallel <- (.Platform$OS.type != "windows")
PB.CI(object = object, alpha = .05, method = "none")