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| 1 | Objective Bayesian Analysis of Degradation Model with Respect to a Wiener Process显示文摘This paper proposes an objective Bayesian method to study the degradation model with respect to a Wiener process.The Jeffreys prior and reference prior for the parameters are derived,and the propriety of the posteriors under these priors is validated.Two sampling algorithms are introduced to compute the posteriors.A simulation study is conducted to investigate the performance of the objective Bayesian procedure.Finally,the authors apply the approach to a degradation data. | HE Lei HE Daojiang CAO Mingxiang | 2016 | Journal of Systems Science & Complexity2016，29，6： | 3 |
| 2 | A NEW PROCEDURE FOR TESTING NORMALITY BASED ON THE L_2 WASSERSTEIN DISTANCE显示文摘This paper proposes a new goodness-of-fit test for normality based on the L_2 Wasserstein distance.The authors first construct a probability through the Bootstrap resampling.Although the probability is not distributed uniformly on the interval(0,1)under the null hypothesis,it is shown that its distribution is free from the unknown parameters,which indicates that such a probability can be taken as the test statistic.It emerges from the simulation study of power that the new test is able to better discriminate between the normal distribution and those distributions with short tails.For such alternatives,it has a substantially better power than existing tests including the Anderson-Darling test and Shapiro-Wilk test,which are two of the best tests for normality.In addition,the sensitivity analysis of tests is also investigated in the presence of moderate perturbation,which shows that the new test is a rather robust test. | HE Daojiang XU Xingzhong ZHAO Jianxin | 2013 | Journal of Systems Science & Complexity2013，26，4： | 2 |
| 3 | Objective Bayesian analysis for the accelerated degradation model usingWiener process with measurement errors显示文摘The Wiener process as a degradation model plays an important role in the degradation analysis.In this paper, we propose an objective Bayesian analysis for an acceleration degradation Wienermodel which is subjected to measurement errors. The Jeffreys prior and reference priors underdifferent group orderings are first derived, the propriety of the posteriors is then validated. It isshown that two of the reference priors can yield proper posteriors while the others cannot. A simulation study is carried out to investigate the frequentist performance of the approach comparedto the maximum likelihood method. Finally, the approach is applied to analyse a real data. | Daojiang He Yunpeng Wang Mingxiang Cao | 2018 | Statistical Theory and Related Fields2018，2，1： | 1 |
| 4 | Step-stress accelerated degradation test planning based on Wiener processwith correlation显示文摘To assess the lifetime distribution of highly reliable or expensive product,one of the most commonly used strategies is to construct step-stress accelerated degradation test(SSADT)which can curtail the test duration and reduce the test cost.In reality,it is not unusual for a unit with a higher degradation rate which exhibits a more volatile degradation path.Recently,Ye,Chen,and Shen[(2015).A new class of Wiener process models for degradation analysis.Reliability Engineering and System Safety,139,58–67]proposed a Wiener process to capture the positive correlation between the drift rate and the volatility.In this paper,an optimal SSADT plan is developed under the assumption that the underlying degradation path follows the Wiener process with correlation.Firstly,the stochastic diffusion process is introduced to model a typical SSADT problem.Then the design variables,including the sample size,the measurement frequency and the numbers of measurements under each stress level,are optimised by minimising the asymptotic variance of the estimated p-percentile of the product’s lifetime distribution subject to the total experimental cost not exceeding a pre-specified budget.Finally,a numerical example is presented to illustrate the proposed method. | Lei He Rong-Xian Yue Daojiang He | 2018 | Statistical Theory and Related Fields2018，2，1： | 1 |
| 5 | Admissibility of Linear Predictors in the Superpopulation Model with Respect to Inequality Constraints under Matrix Loss Function显示文摘 | Daojiang He Xingzhong Xu | 2011 | Communications in Statistics - Theory and Methods2011，，21： | 1 |
| 6 | Bayesian analysis for the Lomax model using noninformative priors显示文摘The Lomax distribution is an important member in the distribution family.In this paper,we systematically develop an objective Bayesian analysis of data from a Lomax distribution.Noninformative priors,including probability matching priors,the maximal data information(MDI)prior,Jeffreys prior and reference priors,are derived.The propriety of the posterior under each prior is subsequently validated.It is revealed that the MDI prior and one of the reference priors yield improper posteriors,and the other reference prior is a second-order probability matching prior.A simulation study is conducted to assess the frequentist performance of the proposed Bayesian approach.Finally,this approach along with the bootstrap method is applied to a real data set. | Daojiang He Dongchu Sun Qing Zhu | 2023 | Statistical Theory and Related Fields2023，7，1： | 1 |
| 7 | A Stochastic Restricted s–K Estimator in the Linear Model显示文摘In this paper, we propose a stochastic restricted s–K estimator in the linear model with additional stochastic linear restrictions by combining the ordinary mixed estimator(OME) with the s–K estimator. It is shown that the proposed estimator is superior to the OME and the s–K estimator under the mean squared error matrix criterion under some conditions. Finally, a numerical example and a Monte Carlo simulation study are given to verify the theoretical results. | Daojiang HE Yan WU | 2014 | Journal of Mathematical Research with Applications2014，34，3： | 0 |
| 8 | Objective Bayesian hypothesis testing and estimation for the intraclass model显示文摘The intraclass correlation coefficient (ICC) plays an important role in various fields of study asa coefficient of reliability. In this paper, we consider objective Bayesian analysis for the ICCin the context of normal linear regression model. We first derive two objective priors for theunknown parameters and show that both result in proper posterior distributions. Within aBayesian decision-theoretic framework, we then propose an objective Bayesian solution to theproblems of hypothesis testing and point estimation of the ICC based on a combined use of theintrinsic discrepancy loss function and objective priors. The proposed solution has an appealinginvariance property under one-to-one reparametrisation of the quantity of interest. Simulationstudies are conducted to investigate the performance the proposed solution. Finally, a real dataapplication is provided for illustrative purposes. | Duo Zhang Daojiang He Xiaoqian Sun Tao Lu Min Wang | 2018 | Statistical Theory and Related Fields2018，2，1： | 0 |
| 9 | A High-Dimensional Test for Multivariate Analysis of Variance Under a Low-Dimensional Factor Structure显示文摘In this paper,the problem of high-dimensional multivariate analysis of variance is investigated under a low-dimensional factor structure which violates some vital assumptions on covariance matrix in some existing literature.We propose a new test and derive that the asymptotic distribution of the test statistic is a weighted distribution of chi-squares of 1 degree of freedom under the null hypothesis and mild conditions.We provide numerical studies on both sizes and powers to illustrate performance of the proposed test. | Mingxiang Cao Yanling Zhao Kai Xu Daojiang He Xudong Huang | 2022 | Communications in Mathematics and Statistics2022，10，4： | 0 |
| 10 | Admissible Linear Estimators of Multivariate Regression Coefcient with Respect to an Inequality Constraint under Balanced Loss Function显示文摘In this paper,the admissibility of multivariate linear regression coefcient with respect to an inequality constraint under balanced loss function is investigated.Necessary and sufcient conditions for admissible homogeneous and inhomogeneous linear estimators are obtained,respectively. | Jie WU Daojiang HE | 2013 | Journal of Mathematical Research with Applications2013，33，6： | 0 |
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