ci: Confidence Interval

In HDCI: High Dimensional Confidence Interval Based on Lasso and Bootstrap

Description

Gets bootstrap confidence intervals for each of the coefficients of variables/predictors.

Usage

ci(Beta, Beta_bootstrap, alpha = 0.05, type = c("basic", "quantile", "bca", "basic2"), 
   a, Beta2)

Arguments

Beta	An estimate of the coefficients.
Beta_bootstrap	Bootstrap estimates of the coefficients – a B by p matrix, where B is the number of replications in the bootstrap and p is number of variables/predictors.
alpha	Significance level – default is 0.05.
type	Different type of confidence interval: basic, quantile, bca (adjusted bootstrap confidence intervals) and basic2 (a modified basic confidence interval).
a	Parameter in the bca confidence interval.
Beta2	An estimator of the coefficients used in the basic2 confidence interval.

Value

interval

A 2 by p matrix containing the confidence intervals – the first row is the lower bounds of the confidence intervals for each of the coefficients and the second row is the upper bounds of the confidence intervals.

HDCI documentation built on May 2, 2019, 4:48 a.m.