It is shown that, in a very general setting, the empirical likelihood method for constructing
confidence intervals is Bartlett-correctable. This means that a simple adjustment for the …

Computing a profile empirical likelihood function, which involves constrained maximization,
is a key step in applications of empirical likelihood. However, in some situations, the …

We describe the main features of empirical likelihood and discuss recent developments,
including Bartlett correction and location adjustment. Algorithms are provided for …

It is proved that, except for a location term, empirical likelihood does draw contours which
are second-order correct for those of a pseudo-likelihood. However, except in the case of …

It is well known that we can use the likelihood ratio statistic to test hypotheses and to
construct confidence intervals in full parametric models. Recently, Owen introduced the …

The empirical distribution function based on a sample is well known to be the maximum
likelihood estimate of the distribution from which the sample was taken. In this paper the …

Standard empirical likelihood confidence intervals for quantiles are identical to sign-test
intervals. They have relatively large coverage error, of size n-1/2, even though they are two …

The standard multivariate normal approximation to the distribution of the signed root of the
empirical likelihood ratio statistic is considered in cases where inference is required for a …

Nonparametric versions of Wilks′ theorem are proved for empirical likelihood estimators of
slope and mean parameters for a simple linear regression model. They enable us to …

The method of empirical likelihood can be viewed as one of allocating probabilities to an n-
cell contingency table so as to minimise a goodness-of-fit criterion. It is shown that, when the …