supported by the National Natural Science Foundation of China(11271088,11361011,11201088);the Natural Science Foundation of Guangxi(2013GXNSFAA019004,2013GXNSFAA019007,2013GXNSFBA019001)
The empirical likelihood is used to propose a new class of quantile estimators in the presence of some auxiliary information under positively associated samples. It is shown that the proposed quantile estimators are a...
The paper introduces a new class of numerical schemes for the approximate solutions of stochastic pantograph equations. As an effective technique to implement implicit stochastic methods, strong predictor-corrector me...
Supported by the National Natural Science Foundation of China(No.11271088,11361011,11201088);Natural Science Foundation of Guangxi(No.2013GXNSFAA(019004 and 019007),2013GXNSFBA019001)
Oonsider two linear models Xi = U'β + ei, Yj = V1/2y + ηj with response variables missing at random. In this paper, we assume that X, Y are missing at random (MAR) and use the inverse probability weighted imput...
Supported by the National Natural Science Foundation of China(11271088,11361011,11201088);the Natural Science Foundation of Guangxi(2013GXNSFAA019004,2013GXNSFAA019007,2013GXNSFBA019001)
In this paper, we obtain the joint empirical likelihood confidence regions for a finite number of quantiles under strong mixing samples. As an application of this result, the empirical likelihood confidence intervals ...
Supported by the National Natural Science Foundation of China(No.11271088,11201088,11361011);the Natural Science Foundation of Guangxi(N0.2013GXNSFAA019004,2013GXNSFAA019007,2013GXNSFBA019001);the New Century Ten,Hundred and Thousand Talents Project of Guangxi;the Youth Foundation of Guangxi Normal University
The construction of confidence intervals for quantiles of a population under a associated sample is studied by using the blockwise technique. It is shown that the blockwise empirical likelihood (EL) ratio statistic ...
Supported by the National Natural Science Foundation of China(No.11271088,11361011,11201088);Guangxi"Bagui Scholar"Special Project Foundation;the Natural Science Foundation of Guangxi(No.2013GXNS-FAA019004,2013GXNSFAA019007,2013GXNSFBA019001)
Suppose that we have a partially linear model Yi = xiβ + g(ti) +εi with independent zero mean errors εi, where (xi,ti, i = 1, ... ,n} are non-random and observed completely and (Yi, i = 1,...,n} are missing a...
the National Natural Science Foundation of China(11271088,11201088);the Guangxi"Bagui Scholar"Special Project Foundation;the Natural Science Foundation of Guangxi(2013GXNSFAA019004,2013GXNSFAA019007,2013GXNSFBA019001)