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Abstract: Empirical likelihood methods based on some weighted score equations are proposed for constructing confidence intervals for the coefficient in the simple bilinear model without assuming normality for the errors and without estimating the asymptotic variance explicitly. A simulation study confirms the good finite sample behavior of the proposed methods. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a flexible model for cyclic abundance data, that takes into account predator–prey interactions. The idea is to incorporate a predator–prey dynamical model into a non homogeneous Poisson process of periodic intensity rate. Further, we devise an easy to implement estimation method and derive asymptotic confidence intervals. Finally, a simulation study indicates that the method performs well for small samples which are typical in ecology. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate the estimation of conditional density function based on the single-index model for functional time series data. The asymptotic normality of the conditional density estimator and the conditional mode estimator for the mixing dependence functional time series data are obtained, respectively. Furthermore, as applications, the asymptotic confidence interval of the conditional density function and the conditional mode are also presented for . [Copyright &y& Elsevier]

Abstract: For distributed as normal or lognormal, the interval estimation of the mean and variance of the corresponding limited or truncated random variable is addressed using the concept of a generalized confidence interval, based on a sample from the distribution of . Numerical results and practical examples are used to illustrate the results. [Copyright &y& Elsevier]

Abstract: Omelka [Omelka, M., 2007. Second-order linearity of Wilcoxon rank statistics. Ann. Inst. Statist. Math. 59, 385–402] proposed an alternative way of constructing a confidence interval based on -estimators for single parameters in linear models. We will compare this confidence interval with a traditional (Wald type) confidence interval theoretically as well as by means of a Monte Carlo experiment. As a by-product we will show the asymptotic normality of the estimator of proposed in [Koul, H.L., Sievers, G.L., McKean, J., 1987. An estimator of the scale parameter for the rank analysis of linear models under general score functions. Scand. J. Statist. 14, 131–141] under somewhat different assumptions from those in [Thewarepperuma, P.S., 1987. On estimation of some density functionals under regression and one sample models. Ph.D. Thesis. Michigan State University, Department of Statistics and Probability]. [Copyright &y& Elsevier]