confint: Calculate confidence intervals

In complmrob: Robust Linear Regression with Compositional Data as Covariates

Description

Calculate confidence intervals for bootstrapped robust linear regression estimates with or without compositional data

Usage

## S3 method for class 'bccomplmrob'
confint(object, parm, level = 0.95,
  type = c("bca", "perc", "norm", "basic", "stud"), ...)

## S3 method for class 'bclmrob'
confint(object, parm, level = 0.95, type = c("bca",
  "perc", "norm", "basic", "stud"), ...)

Arguments

object	an object returned from bootcoefs.
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level	the confidence level required.
type	the type of interval required (see the type argument of boot.ci).
...	currently ignored.

Methods (by class)

• bccomplmrob: for bootstrapped estimates of robust linear regression models for compositional data

• bclmrob: for bootstrapped estimates of robust linear regression models

Examples

data <- data.frame(lifeExp = state.x77[, "Life Exp"], USArrests[ , -3])
mUSArr <- complmrob(lifeExp ~ ., data = data)
bc <- bootcoefs(mUSArr, R = 200) # the number of bootstrap replicates should
                                 # normally be higher!
confint(bc, level = 0.95, type = "perc")

### For normal robust linear regression models ###
require(robustbase)
data(aircraft)

mod <- lmrob(Y ~ ., data = aircraft)
bootEst <- bootcoefs(mod, R = 200)
confint(bootEst, level = 0.95, type = "perc")

Example output

                2.5 %    97.5 %
(Intercept) 65.876663 74.368813
Murder      -3.399352 -1.415439
Assault     -2.738976  1.022458
Rape         2.001424  4.400795
Loading required package: robustbase
             2.5 %       97.5 %
[1,] -13.677461260 22.481053820
[2,]  -5.329997929 -0.711657719
[3,]  -0.573129798  7.812296663
[4,]  -0.001130836  0.003389875
[5,]  -0.001994485  0.001278911

complmrob documentation built on Sept. 18, 2019, 1:02 a.m.