Empirical likelihood is a popular nonparametric analog of the usual parametric likelihood,
inheriting many of the large-sample properties of the latter construct. This article presents a …

Supplement to the paper:“Two-step semiparametric empirical likelihood inference”. The
supplement contains four appendices: Appendix A gathers all the proofs for the examples …

This paper considers the efficient estimation of copula-based semiparametric strictly
stationary Markov models. These models are characterized by nonparametric invariant (one …

Suppose that X1,…, Xn is a sequence of independent random vectors, identically distributed
as ad‐dimensional random vector X. Let be a parameter of interest and be some nuisance …

In this paper we propose a smoothed jackknife empirical likelihood method to construct
confidence intervals for the receiver operating characteristic (ROC) curve. By applying the …

For regression analysis of interval-censored failure time data, Zhang et al.(2005)[40]
proposed an estimating equation approach to fit linear transformation models. In this paper …

Empirical likelihood is a very powerful nonparametric tool that does not require any
distributional assumptions. showed that in Bayesian inference, if one replaces the usual …

In this paper, we apply smoothed jackknife empirical likelihood (JEL) method to construct
confidence intervals for the receiver operating characteristic (ROC) curve with missing data …

For the comparison of two diagnostic markers at a flexible specificity, people apply the
difference of two correlated receiver operating characteristic (ROC) curves to identify the …

Copulas are becoming a quite flexible tool in modeling dependence among the components
of a multivariate vector. In order to predict extreme losses in insurance and finance, extreme …