hd.uni: Hellinger distance between unimodal densities

In nilanjanalaha/SDNNtests: SHAPE CONSTRAINED TESTS OF STOCHASTIC DOMINANCE

Description

Provides an estimate of the squared hellinger distance between the densities underlying the (two) observed samples. This estimator assumes that both underlying densities are unimodal. . This function uses the density estimator of Birges (1997), given by calc_mode. See Laha et al. (2021) for more details.

Usage

hd.uni(x, y)

Arguments

x	Vector of m independent and identically distributed random variables; corresponds to the first sample.
y	Vector of n independent and identically distributed random variables; corresponds to the second sample.

Details

This function calls link{calc_mode} where the parameter t is taken to be one.

Value

An estimate of the Hellinger distance between the densities of x and y.

Author(s)

Nilanjana Laha (maintainer), [e-mail],

Alex Luedtke, [e-mail].

References

Laha, N., Moodie, Z., Huang, Y., and Luedtke, A. (2021). Improved inference for vaccine-induced immune responses via shape-constrained methods. Submitted.

Birge, L. (1997). Estimation of unimodal densities without smoothness assumptions, Ann. Statist., 25, 970–981.

See Also

calc_mode, hd.lc, hd.lc.sm, hell.ci

Examples

x <- sort(rnorm(100)); y <- sort(rgamma(50, shape=1));
hd.uni(x,y)

nilanjanalaha/SDNNtests documentation built on June 15, 2021, 8:20 p.m.