Exponential empirical likelihood for a one sample mean vector hypothesis testing {Rfast}

Exponential empirical likelihood for a one sample mean vector hypothesis testing

Description

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

Usage

mv.eeltest1(x, mu, tol = 1e-06)

Arguments

x

A matrix containing Euclidean data.

mu

The hypothesized mean vector.

tol

The tolerance value used to stop the Newton-Raphson algorithm.

Details

Multivariate hypothesis test for a one sample mean vector. This is a non parametric test and it works for univariate and multivariate data. The p-value is currently computed only asymptotically (no bootstrap calibration at the moment).

Value

A list including:

p

The estimated probabiities.

lambda

The value of the Lagrangian parameter \lambda.

iters

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.

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

james, mv.eeltest2

Examples

x <- Rfast::rmvnorm(100, numeric(10), diag( rexp(10, 0.5) ) )
res<-mv.eeltest1(x, numeric(10) )