bootPaired {CarletonStats}  R Documentation 
Perform a bootstrap of two paired variables.
bootPaired(x, ...) ## Default S3 method: bootPaired(x, y, conf.level = 0.95, B = 10000, plot.hist = TRUE, plot.qq = FALSE, legend.loc = "topright", x.name = deparse(substitute(x)), y.name = deparse(substitute(y)), ...) ## S3 method for class 'formula' bootPaired(formula, data, subset, ...)
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 resamples (positive integer greater than 2). 
plot.hist 
logical. If 
plot.qq 
logical. If 
legend.loc 
location for the legend on the histogram. Options are

x.name 
Label for variable x 
y.name 
Label for variable y 
formula 
a formula 
data 
a data frame that contains the variables given in the formula. 
subset 
an optional expression indicating what observations to use. 
The command will compute the difference of x
and y
and
bootstrap the difference. The mean and standard error of the bootstrap
distribution will be printed as well as a bootstrap percentile interval.
Observations with missing values are removed.
The command invisibly returns a vector with the replicates of the statistic being bootstrapped.
default
: Perform a bootstrap of two paired variables.
formula
: Perform a bootstrap of two paired variables.
Laura Chihara
Tim Hesterberg's website http://www.timhesterberg.net/bootstrap
#Bootstrap the mean difference of fat content in vanilla and chocolate ice #cream. Data are paired becaues ice cream from the same manufacturer will #have similar content. Icecream bootPaired(ChocFat ~ VanillaFat, data = Icecream) bootPaired(Icecream$VanillaFat, Icecream$ChocFat)