quantile_vcov: Variance-Covariance of Quantiles

In QuantileGH: Quantile Least Mahalanobis Distance Estimator for Tukey g-&-h Mixture

Variance-Covariance of Quantiles

Description

To compute the variance-covariance matrix of quantiles based on Theorem 1 and 2 of Mosteller (1946).

Usage

quantile_vcov(p, d)

Arguments

p	numeric vector, cumulative probabilities at the given quantiles
d	numeric vector, probability densities at the given quantiles

Details

The end user should make sure no density too close to 0 is included in argument d.

Function quantile_vcov must not be used in a compute-intensive way.

Value

Function quantile_vcov returns the variance-covariance matrix of quantiles.

References

Frederick Mosteller. On Some Useful "Inefficient" Statistics (1946). \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1214/aoms/1177730881")}

QuantileGH documentation built on May 29, 2024, 12:14 p.m.