Exponential empirical likelihood for a one sample mean vector hypothesis testing: 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
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.
Details
Multivariate hypothesis test for a one sample mean vector. This is a non parametric test and it works for univariate and multivariate data.
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.