kendall: Estimates the Kendall rank correlation coefficient

In hermiter: Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Nonparametric Correlation (Bivariate)

Estimates the Kendall rank correlation coefficient

Description

This method calculates the Kendall rank correlation coefficient value. It is only applicable to the bivariate Hermite estimator i.e. est_type = "bivariate".

Usage

kendall(h_est_obj, clipped = FALSE)

Arguments

h_est_obj	A hermite_estimator_bivar object.
clipped	A boolean value. Indicates whether to clip the Kendall rank correlation estimates to lie between -1 and 1.

Details

The object must be updated with observations prior to the use of this method.

Value

A numeric value.

Examples

## Not run: 
hermite_est <- hermite_estimator(N = 10, standardize = TRUE,
est_type="bivariate", observations = matrix(rnorm(30*2), nrow=30, 
ncol=2, byrow = TRUE))
kendall_est <- kendall(hermite_est)

## End(Not run)

hermiter documentation built on May 31, 2023, 6:30 p.m.