spearmans: Estimates the Spearman's 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 Spearman's rank correlation coefficient

Description

This method utilizes the estimator (8) in the paper Stephanou, Michael and Varughese, Melvin. "Sequential estimation of Spearman rank correlation using Hermite series estimators." Journal of Multivariate Analysis (2021) <doi:10.1016/j.jmva.2021.104783> to calculate the Spearman rank correlation coefficient. It is only applicable to the bivariate Hermite estimator i.e. est_type = "bivariate".

Usage

spearmans(h_est_obj, clipped = FALSE)

Arguments

h_est_obj	A hermite_estimator_bivar object.
clipped	A boolean value. Indicates whether to clip Spearman's 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))
spearmans_est <- spearmans(hermite_est)

## End(Not run)

hermiter documentation built on May 29, 2024, 2:09 a.m.