Log-likelihood ratio test for a Dirichlet mean vector.
dirimean.test(x, a)A matrix with the compositional data. No zero values are allowed.
A compositional mean vector. The concentration parameter is estimated at first. If the elements do not sum to 1, it is assumed that the Dirichlet parameters are supplied.
If there are no zeros in the data, a list including:
A matrix with the estimated parameters under the null and the alternative hypothesis.
The log-likelihood under the alternative and the null hypothesis.
The value of the test statistic and its relevant p-value.
Log-likelihood ratio test is performed for the hypothesis the given vector of parameters "a" describes the compositional data well.
Ng Kai Wang, Guo-Liang Tian and Man-Lai Tang (2011). Dirichlet and related distributions: Theory, methods and applications. John Wiley \& Sons.
# NOT RUN {
x <- rdiri( 100, c(1, 2, 3) )
dirimean.test(x, c(1, 2, 3) )
dirimean.test( x, c(1, 2, 3)/6 )
# }
Run the code above in your browser using DataLab