wBoot (version 1.0.3)

boot.cond.mean.bca: BCa Bootstrap Conditional Mean CI in Simple Linear Regression

Description

Determines a confidence interval for a conditional mean in simple linear regression, using the BCa bootstrap method.

Usage

boot.cond.mean.bca(x, y, xp, conf.level = 0.95, R = 9999)

Arguments

x

a (non-empty) numeric vector of predictor-variable data values.

y

the corresponding numeric vector of response-variable data values.

xp

the value of the predictor variable for which to find the CI for the conditional mean of the response variable.

conf.level

the confidence level (between 0 and 1); default is 0.95.

R

the number of bootstrap replications; default is 9999.

Value

• A list with class "boot.regcor" containing the following components:
• Boot.values
  the point estimates (fits) obtained from the bootstrap.
• Confidence.limits
  the upper and lower limits of the confidence interval.
• Header
  the main title for the output.
• Variable.1
  the predictor variable.
• Variable.2
  the response variable.
• n
  the sample size.
• Statistic
  the name of the statistic, here fit.
• Observed
  the observed point estimate (fit).
• Replications
  the number of bootstrap replications.
• Mean
  the mean of the bootstrap values.
• SE
  the standard deviation of the bootstrap values.
• Bias
  the difference between the mean of the bootstrap values and the observed value.
• Percent.bias
  the percentage bias: 100*|Bias/Observed|.
• Null
  always NULL for this function.
• Alternative
  always NULL for this function.
• P.value
  always NULL for this function.
• p.value
  always NULL for this function.
• Level
  the confidence level.
• Type
  always NULL for this function.
• Confidence.interval
  the confidence interval.
• cor.ana
  a logical; always FALSE for this function.

concept

• Bootstrap
• BCa bootstrap
• Simple linear regression
• Confidence interval
• Conditional mean in simple linear regression

Examples

# Lot size, house size, and value for a sample of homes in a particular area.
data("homes")
str(homes)
attach(homes)

# 95% (default) CI for the conditional mean value of a 3000 sq.ft. home,
# with 999 bootstrap replications.
boot.cond.mean.bca(HOUSE.SIZE, VALUE, 3000, R = 999)

# 90% CI for the conditional mean value of a 3000 sq.ft. home, with
# 999 bootstrap replications.
boot.cond.mean.bca(HOUSE.SIZE, VALUE, 3000, conf.level = 0.90, R = 999)

detach(homes) # clean up