eel.test1: Exponential empirical likelihood for a one sample mean vector...

In Compositional: Compositional Data Analysis

Exponential empirical likelihood for a one sample mean vector hypothesis testing

Description

Exponential empirical likelihood for a one sample mean vector hypothesis testing.

Usage

eel.test1(x, mu, tol = 1e-06, R = 1)

Arguments

x	A matrix containing Euclidean data.
mu	The hypothesized mean vector.
tol	The tolerance value used to stop the Newton-Raphson algorithm.
R	The number of bootstrap samples used to calculate the p-value. If R = 1 (default value), no bootstrap calibration is performed

Details

Multivariate hypothesis test for a one sample mean vector. This is a non-parametric test and it works for univariate and multivariate data.

Value

A list including:

p	The estimated probabilities.
lambda	The value of the Lagrangian parameter \lambda.
iter	The number of iterations required by the newton-Raphson algorithm.
info	The value of the log-likelihood ratio test statistic along with its corresponding p-value.
runtime	The runtime of the process.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Jing Bing-Yi and Andrew TA Wood (1996). Exponential empirical likelihood is not Bartlett correctable. Annals of Statistics 24(1): 365-369.

Owen A. B. (2001). Empirical likelihood. Chapman and Hall/CRC Press.

See Also

el.test1, hotel1T2, james, hotel2T2, maov, el.test2, comp.test

Examples

x <- Rfast::rmvnorm(100, numeric(10), diag( rexp(10, 0.5) ) )
eel.test1(x, numeric(10) )
el.test1(x, numeric(10) )

Compositional documentation built on Oct. 23, 2023, 5:09 p.m.