bootSlope {CarletonStats}R Documentation

Bootstrap the slope of a simple linear regression line

Description

Bootstrap theslope of a simple linear regression line. The bootstrap mean and standard error are printed as well as a bootstrap percentile confidence interval.

Usage

bootSlope(x, ...)

## Default S3 method:
bootSlope(
  x,
  y,
  conf.level = 0.95,
  B = 10000,
  plot.hist = TRUE,
  xlab = NULL,
  ylab = NULL,
  title = NULL,
  plot.qq = FALSE,
  x.name = deparse(substitute(x)),
  y.name = deparse(substitute(y)),
  seed = NULL,
  ...
)

## S3 method for class 'formula'
bootSlope(formula, data, subset, ...)

Arguments

x

a numeric vector.

...

further arguments to be passed to or from methods.

y

a numeric vector.

conf.level

confidence level for the bootstrap percentile interval.

B

number of times to resample (positive integer greater than 2).

plot.hist

a logical value. If TRUE, plot the bootstrap distribution of the resampled slope.

xlab

an optional character string for the x-axis label

ylab

an optional character string for the y-axis label

title

an optional character string giving the plot title

plot.qq

a logical value. If TRUE a normal quantile-quantile plot of the bootstraped values is created.

x.name

Label for variable x

y.name

Label for variable y

seed

optional argument to set.seed

formula

a formula of the form lhs ~ rhs where lhs is a numeric variable giving the data values and rhs a factor with two levels giving the corresponding groups.

data

an optional data frame containing the variables in the formula formula. By default the variables are taken from environment(formula).

subset

an optional vector specifying a subset of observations to be used.

Details

Observations with missing values are removed.

Value

The command returns the slopes of the resampled observations.

Methods (by class)

Author(s)

Adam Loy, Laura Chihara

References

Tim Hesterberg's website https://www.timhesterberg.net/bootstrap-and-resampling

Examples



plot(states03$ColGrad, states03$InfMortality)
bootSlope(InfMortality ~ ColGrad, data = states03, B = 1000)
bootSlope(states03$ColGrad, states03$InfMortality, B = 1000)


[Package CarletonStats version 2.2 Index]