lancor (version 0.1.2)

lcor.ci: confidence intervals for the Lancaster correlation coefficient

Description

Computes confidence intervals for the Lancaster correlation coefficient. Lancaster correlation is a bivariate measures of dependence.

Usage

lcor.ci(x, y = NULL, conf.level = 0.95, type = c("rank", "linear"), con = TRUE,
        R = 1000, method = c("plugin", "boot", "pretest"))

Value

lcor.ci returns a vector containing the lower and upper limits of the confidence interval.

Arguments

x

a numeric vector, or a matrix or data frame with two columns.

y

NULL (default) or a vector with same length as x.

conf.level

confidence level of the interval.

type

a character string indicating which lancaster correlation is to be computed. One of "rank" (default), or "linear": can be abbreviated.

con

logical; if TRUE (default), conservative asymptotic confidence intervals are computed.

R

number of bootstrap replications.

method

a character string indicating how the asymptotic covariance matrix is computed if type ="linear". One of "plugin" (default), "boot" or "symmetric": can be abbreviated.

Author

Hajo Holzmann, Bernhard Klar

References

Holzmann, Klar (2024) Lancester correlation - a new dependence measure linked to maximum correlation. arXiv:2303.17872

See Also

lcor, lcor.comp, lcor.test

Examples

n <- 1000
x <- matrix(rnorm(n*2), n)
nu <- 2
y <- x / sqrt(rchisq(n, nu)/nu) # multivariate t
lcor(y, type = "rank")
lcor.ci(y, type = "rank")