bootCor {CarletonStats} | R Documentation |
Bootstrap the correlation of two numeric variables.
bootCor(x, ...) ## Default S3 method: bootCor(x, y, conf.level = 0.95, B = 10000, plot.hist = TRUE, hist.title = NULL, plot.qq = FALSE, legend.loc = "topright", x.name = deparse(substitute(x)), y.name = deparse(substitute(y)), ...) ## S3 method for class 'formula' bootCor(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 ercentile interval. |
B |
number of times to resample (positive integer greater than 2). |
plot.hist |
a logical value. If |
hist.title |
a user supplied title for the histogram. |
plot.qq |
a logical value. If |
legend.loc |
location to place the legend. Options include
|
x.name |
Label for variable x |
y.name |
Label for variable y |
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. |
Bootstrap the correlation of two numeric variables. The bootstrap mean and standard error are printed as well as a bootstrap percentile confidence interval.
Observations with missing values are removed.
The command invisibly returns the correlations of the resampled observations.
default
: Bootstrap the correlation of two numeric variables.
formula
: Bootstrap the correlation of two numeric variables.
Laura Chihara
Tim Hesterberg's website http://www.timhesterberg.net/bootstrap
plot(states03$ColGrad, states03$InfMortality) bootCor(InfMortality ~ ColGrad, data = states03) bootCor(states03$ColGrad, states03$InfMortality)