We show that empirical likelihood is justified as a method of inference for a class of models
much larger than the class of linear models considered by Owen (1991). In particular, we …

The paper considers improving the efficiency of parameter estimation of the quasi-likelihood
in generalized linear models. The improvement is offered by employing the empirical …

In this paper, we consider the application of the empirical likelihood method to partially
linear model. Unlike the usual cases, we first propose an approximation to the residual of the …

The quasi-likelihood function proposed by Wedderburn broadened the scope of generalized
linear models by specifying the variance function in-stead of the entire distribution. However …

Empirical likelihood is a nonparametric method of inference. It has sampling properties
similar to the bootstrap, but where the bootstrap uses resampling, it profiles a multinomial …

Generalized linear models are further generalized to include a linear predictor for the
dispersion as well as for the mean. It is shown how the convenient structure of generalized …

Improved Likelihood Ratio Statistics for Generalized Linear Models Page 1 JR Statist. Soc. B
(1983), 45,No. 3,pp. 404-413 Improved Likelihood Ratio Statistics for Generalized Linear …

We extend the empirical likelihood of Owen [Ann. Statist. 18 (1990) 90–120] by partitioning
its domain into the collection of its contours and mapping the contours through a continuous …

This paper studies the method of empirical likelihood in models with weakly dependent
processes. In such cases, if the likelihood function is formulated as if the data process were …

Empirical likelihood provides inferences whose validity does not depend on specifying a
parametric model for the data. Because it uses a likelihood, the method has certain inherent …