The Incremental Group Testing Model for Gap Closing in Sequencing Long Molecules

In this paper, we propose the incremental group testing model for the gap closing problem, which assumes that we can tell the difference between the outcome of testing a subset S, and the outcome of testing S {x}. We also give improvements over currently best results in literature for some other models.     

我国海洋国土可持续开发探讨

论述我国海洋国土开发的战略意义,阐明了我国海洋资源条件,开发现状及存在问题,提出了可持续开发的对策。     

需求牵引课题培养材料领域研究生爱国担当之志

培养研究生爱国担当之志是研究生教育的根本,是科研育人的生动体现,是落实全国高校思想政治工作会议精神与全国研究生教育会议精神的核心。以材料领域研究生培养为例,探讨需求牵引课题激发与培养研究生爱国担当之志的路径与成效。结合自主创新研究成果与航天迫切需求,激发学生奉献与担当之志,立志为我国航天强国事业贡献青春与力量,担当时代赋予的重任。实现将科学研究与思想引领有机融合,引导学生建立主动将个人成长与国家发展和中华民族伟大复兴相结合的信念,培养学生既具有过硬材料创新本领,又具有自信、爱国、奉献、担当意识,为中国特色社会主义现代化建设培养德才兼备的材料领域创新拔尖领军人才。     

Box-Cox变换下联合均值与方差模型的极大似然估计

在提出Box-Cox变换下联合均值与方差模型的基础上,研究了该模型参数的估计问题.同时利用截面极大似然估计方法对变换参数λ进行估计,并对均值模型和方差模型的参数进行极大似然估计.通过随机模拟和实例研究,结果表明该模型和方法是有效和可行的.     

Regularization and variable selection for infinite variance autoregressive models

Autoregressive models with infinite variance are of great importance in modeling heavy-tailed time series and have been well studied. In this paper, we propose a penalized method to conduct model selection for autoregressive models with innovations having Pareto-like distributions with index α∈(0,2)$\alpha \in (\mathrm{0,2})$. By combining the least absolute deviation loss function and the adaptive lasso penalty, the proposed method is able to consistently identify the true model and at the same time produce efficient estimators with a convergence rate of n^−1/α$n^{-1/\alpha }$. In addition, our approach provides a unified way to conduct variable selection for autoregressive models with finite or infinite variance. A simulation study and a real data analysis are conducted to illustrate the effectiveness of our method.     

Bayesian inference under progressive type-I interval censoring

Bayesian estimation for population parameter under progressive type-I interval censoring is studied via Markov Chain Monte Carlo (MCMC) simulation. Two competitive statistical models, generalized exponential and Weibull distributions for modeling a real data set containing 112 patients with plasma cell myeloma, are studied for illustration. In model selection, a novel Bayesian procedure which involves a mixture model is proposed. Then the mix proportion is estimated through MCMC and used as the model selection criterion.     

SAM平衡的SG-RAS与SG-CE方法

随机cross entropy(Robinson et al.,2001)方法是目前用于平衡社会核算矩阵的最主流方法,本文综合其与GRAS(Lenzen et al.,2007)方法的思想,扩展提出了SG-CE(stochastic generalized CE)与SG-RAS方法,避免了原始CE方法在平衡SAM时需要对负值元素进行预处理的步骤,试图改进由此引致的缺陷并提高平衡SAM质量。在此基础上,本文运用SG-RAS、SG-CE、CE以及国内常用的余量法对中国2007年SAM进行了平衡,实证结果的对比表明:在平衡系数SAM时,SG-RAS优势非常明显;而平衡流量SAM时,除SG-RAS之外,余量法也具较好表现;但无论是平衡系数还是流量SAM,SG-CE的效果只能说差强人意,原始CE方法更差。     

Creating catalogues of two-level nonregular fractional factorial designs based on the criteria of generalized aberration

We consider the problem of constructing good two-level nonregular fractional factorial designs. The criteria of minimum G and G₂ aberration are used to rank designs. A general design structure is utilized to provide a solution to this practical, yet challenging, problem. With the help of this design structure, we develop an efficient algorithm for obtaining a collection of good designs based on the aforementioned two criteria. Finally, we present some results for designs of 32 and 40 runs obtained from applying this algorithmic approach.     

Generalized quasi-likelihood

The quasi-score function, as defined by Wedderburn (1974) and McCullagh (1983) and so on, is a linear function of observations. The generalized quasi-score function introduced in this paper is a linear function of some unbiased basis functions, where the unbiased basis functions may be some linear functions of the observations or not, and can be easily constructed by the meaning of the parameters such as mean and median and so on. The generalized quasi-likelihood estimate obtained by such a generalized quasi-score function is consistent and has an asymptotically normal distribution. As a result, the optimum generalized quasi-score is obtained and a method to construct the optimum unbiased basis function is introduced. In order to construct the potential function, a conservative generalized estimating function is defined. By conservative, a potential function for the projected score has many properties of a log-likelihood function. Finally, some examples are given to illustrate the theoretical results. This paper is supported by NNSF project (10371059) of China and Youth Teacher Foundation of Nankai University.     

Bayesian analysis of mixture modelling using the multivariate t distribution

A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data.