泊松逆高斯回归模型的贝叶斯统计推断

本文研究泊松逆高斯回归模型的贝叶斯统计推断.基于应用Gibbs抽样,Metropolis-Hastings算法以及Multiple-Try Metropolis算法等MCMC统计方法计算模型未知参数和潜变量的联合贝叶斯估计,并引入两个拟合优度统计量来评价提出的泊松逆高斯回归模型的合理性.若干模拟研究与一个实证分析说明方...     

高血压性脑出血再发生因素的Logistic分析

根据问题的特点 ,选择 Logistic判别模型 ,并借鉴普通线性回归的逐步向前法 ,用似然比统计量 ( Deviance)来筛选自变量 (因素 ) .结果显示 :在 1 1个因素中 ,有 3个是作用显著的 ,而其中舒张压值极为重要 .为降低再出血率 ,将其控制在 85 mm Hg以下是有效而可行的     

Approximate importance sampling Monte Carlo for data assimilation

Importance sampling Monte Carlo offers powerful approaches to approximating Bayesian updating in sequential problems. Specific classes of such approaches are known as particle filters. These procedures rely on the simulation of samples or ensembles of the unknown quantities and the calculation of associated weights for the ensemble members. As time evolves and/or when applied in high-dimensional settings, such as those of interest in many data assimilation problems, these weights typically display undesirable features. The key difficulty involves a collapse toward approximate distributions concentrating virtually all of their probability on an implausibly few ensemble members.

After reviewing ensembling, Monte Carlo, importance sampling and particle filters, we present some approximations intended to moderate the problem of collapsing weights. The motivations for these suggestions are combinations of (i) the idea that key dynamical behavior in many systems actually takes place on a low dimensional manifold, and (ii) notions of statistical dimension reduction. We illustrate our suggestions in a problem of inference for ocean surface winds and atmospheric pressure. Real observational data are used.     

Parallel bucket sorting on graphics processing units based on convex optimization

We found an interesting relation between convex optimization and sorting problem. We present a parallel algorithm to compute multiple order statistics of the data by minimizing a number of related convex functions. The computed order statistics serve as splitters that group the data into buckets suitable for parallel bitonic sorting. This led us to a parallel bucket sort algorithm, which we implemented for many-core architecture of graphics processing units (GPUs). The proposed sorting method is competitive to the state-of-the-art GPU sorting algorithms and is superior to most of them for long sorting keys.     

方差无穷非线性自回归序列的自加权L_1估计

对具有无穷方差的非线性自回归序列x_t=φ(x_(t-1),x_(t-2),…,x_(t-p),θ) ε_t,E(ε_t~2)=∞,利用局部二次近似和连续函数空间C(R~q)上弱收敛随机过程最小点的渐近性质,证明了若存在δ≥1,使得E|ε_t|~δ<∞成立,则θ满足一定条件的自加权L_1估计θ_(L_1)是渐近正态估计,Wald检验统计量也具有通常的x~2分布,为模型的统计推断提供了理论基础.     

基于小子样理论的坦克扭力轴疲劳寿命分析

基于小子样的思想,探讨扭力轴表面缺陷对其疲劳寿命的影响,有助于进一步找到降低扭力轴表面凹坑对扭力轴疲劳寿命影响的方法.     

Second-order linearity of the general signed-rank statistic

Let X₁,…, X_n be i.i.d. random variables symmetric about zero. Let R_i(t) be the rank of |X_i − tn^−1/2| among |X₁ − tn^−1/2|,…, |X_n − tn^−1/2| and T_n(t) = Σ_{i = 1}ⁿφ((n + 1)⁻¹R_i(t))sign(X_i − tn^−1/2). We show that there exists a sequence of random variables V_n such that sup_{0 ≤ t ≤ 1} |T_n(t) − T_n(0) − tV_n| → 0 in probability, as n → ∞. V_n is asymptotically normal.     

STATISTIC MODELING OF THE CREEP BEHAVIOR OF METAL MATRIX COMPOSITES BASED ON FINITE ELEMENT ANALYSIS

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Total Vertex Irregularity Strength of Dense Graphs

Consider a graph of minimum degree δ and order n. Its total vertex irregularity strength is the smallest integer k for which one can find a weighting such that for every pair of vertices of G. We prove that the total vertex irregularity strength of graphs with is bounded from above by . One of the cornerstones of the proof is a random ordering of the vertices generated by order statistics.     

微蜂窝环境中无线接收信号的特性分析

以微蜂窝系统为背景,研究了以测试射线法和虚拟源射线跟踪法为代表的射线跟踪技术,并用这两种方法对射线跟踪进行建模,分析比较两种模型的优缺点.利用这两种模型对实际情况进行计算,精确地找出所有给定情况的传播路径并可视化;对多波干涉的振幅进行了统计学分析,对宽带多波干涉现象进行了数学建模,并分析了合成波的包络统计特性.