特征值问题协调/非协调有限元后验误差分析

本文研究对称椭圆特征值问题的有限元后验误差估计,包括协调元和非协调元,具有下列特色:(1)对协调/非协调元建立了有限元特征函数uh的误差与相应的边值问题有限元解的误差在局部能量模意义下的恒等关系式,该边值问题的右端为有限元特征值λh与uh的乘积,有限元解恰好为uh.从而边值问题有限元解在能量模意义下的局部后验误差指示子,包括残差型和重构型后验误差指示子,成为有限元特征函数在能量模意义下的局部后验误差指示子.(2)讨论了协调有限元特征函数的基于插值后处理的梯度重构型后验误差估计,对有限元特征函数的导数得到了最大模意义下的渐近准确局部后验误差指示子.     

从概率的定义看数学中的唯心主义和形而上学

在概率论中,围绕概率这个概念,历来存在着唯心主义和唯物主义、辩证法和形而上学的斗争.在有的概率书中,有“先验概率”之类的名称,以区别“后验概率”.特别在有的书上,把概率的古典定义称为“先验概率”,称概率的统计定义为“后验概率”.从唯物主义的观点看来,这不仅是提法上的错误,而是明显地把概率的古典定义说成是先验的,和唯     

基于RDEU模型在贝叶斯决策分析中引人概率权重函数的研究:以Prelec概率权重函数为例

对有后验概率分布的决策问题进行贝叶斯分析,决策个体对概率的估计偏差未在考虑之内,导致不同决策者的分析结果并无差异,针对该问题,基于等级依赖期望效用模型中概率权重函数影响决策的机制,在贝叶斯分析中引入概率权重函数,体现决策个体对概率的不同估计,能很好克服贝叶斯决策分析的不足.以Prelec概率权重函数为例的分析表明概率权重函数的引入合理有效,可提升决策分析的针对性.     

用贝叶斯准则进行多级判别预测粘虫的发生量

应用贝叶斯准则进行多级判别分析，是一种概率预报方法，是一个既有理论依据又简便易行的方法．本文根据贝叶斯后验概率公式导出计算概率计数法，应用该方法预测了湖洲市麦类粘虫发生量．对１９７４至１９８６年资料回报，拟合率达１００％．１９８７至１９８９年３年独立资料试报准确，取得了令人满意的效果．     

从后验概率的应用看Bayes概率的意义

某厂有一条自动化生产线，根据以前的经验知它正常运转的概率是９５％。正常运转时生产９０％的合格品，不正常运转时可生产４０％的合格品。某日进行抽样检查，先抽取了一件产品，检验后发现它是合格品；又抽取了一件产品，检验后发现它是废品。根据两次抽样结果推测一下，生产线属于正常运转的概率有多大。这个问题中生产线正常运转的先验概率是９５％，现在产生了新的信息，即两次抽样中一次是合格品，一次是废品，在获取的这种新信息下，再推算生产线正常运转的概率即是后验概率，后验概率可用Ｂａｙｅｓ公式来计算。用Ａ表示生产线正常…     

体积约束的非局部扩散问题的后验误差分析

本文针对体积约束的非局部扩散问题构造了新的后验误差指示器,证明了后验误差指示器的可靠性以及有效性.数值算例验证了理论结果.     

0-1分布的贝叶斯检验在医疗检查中的应用

本文给出了样本相互独立,但不同分布的情况下后验概率函数的表达式及其与序贯后验概率函数之间的关系。在此基础上,给出了先验分布和条件分布为0-1分布情况下贝叶斯后验概率大小的比较方法,结合贝叶斯检验分析法安排医疗检查,使其在不降低诊断准确率的前提下,节省检查费用,提出了合理安排医疗检查的建议。     

古典概型及程序模拟在“清墩”牌型算法中的应用

清墩是起源于舟山的一种扑克游戏,是地方特色文化的组成部分,但是到目前为止部分游戏规则尚不完善.本文以舟山清墩作为研究对象,先使用数学理论计算部分牌型的先验概率,再通过电脑程序模拟(以C-Free5来实现)统计后验概率,通过对比先验概率和后验概率最终确定该牌型出现的概率值.根据牌型出现概率大小判定牌型的大小,以完善清墩游戏规则,促进地方文化的发扬广大.     

有限元的渐近准确误差估计和局部超收敛性

[1—3]曾系统讨论有限元的局部(内部)超收敛理论,指出:一个局部区域只要剖分好而且解光滑,那么有限元逼近在该区域就有超收敛性。Babuska曾讨论某几种有限元的后验估计和渐近误差估计,但这些可算的后验估计量(也叫误差指示子error estima-tor)表达式复杂,计算麻烦,作自适应处理并不方便。实际上,后验估计与局部超收敛性有着天然的联系。本文证明,凡是有超收敛性的地方都可进行渐近准确误差估计,这种可     

两部分混合回归模型的贝叶斯推断

两部分回归模型在刻画半连续型数据的概率发生机制具有重要作用.本文将经典的两部分回归模型推广到两部分有限混合模型,通过假定多条回归直线的混合来解释分布的不齐一性.在贝叶斯框架内,运用马尔可夫链蒙特卡洛(MCMC)方法来进行后验分析.Polya-Gamma先验被用来对logistic模型进行拟合,同时,Stick-breaking先验用于随机权.这些有助于加速后验抽样.本文对可卡因数据展开实证分析.     

Approximate Maximum a Posteriori with Gaussian Process Priors

A maximum a posteriori method has been developed for Gaussian priors over infinite-dimensional function spaces. In particular, variational equations based on a generalisation of the representer theorem and an equivalent optimisation problem are presented. This amounts to a generalisation of the ordinary Bayesian maximum a posteriori approach which is nontrivial as infinite-dimensional domains do not admit any probability densities. Instead of the gradient of the density, the logarithmic gradient of the probability distribution is used. Galerkin methods are proposed for the approximate solution of the variational equations. In summary, a framework and some foundations are provided which are required for the application of numerical approximation to an important class of machine learning problems.     

Bayesian Inference with Wavelets: Density Estimation

Abstract

We propose a prior probability model in the wavelet coefficient space. The proposed model implements wavelet coefficient thresholding by full posterior inference in a coherent probability model. We introduce a prior probability model with mixture priors for the wavelet coefficients. The prior includes a positive prior probability mass at zero which leads to a posteriori thresholding and generally to a posteriori shrinkage on the coefficients. We discuss an efficient posterior simulation scheme to implement inference in the proposed model. The discussion is focused on the density estimation problem. However, the introduced prior probability model on the wavelet coefficient space and the Markov chain Monte Carlo scheme are general.     

Modeling Variability Order: A Semiparametric Bayesian Approach

In comparing two populations, sometimes a model incorporating a certain probability order is desired. In this setting, Bayesian modeling is attractive since a probability order restriction imposed a priori on the population distributions is retained a posteriori. Extending the work in Gelfand and Kottas (2001) for stochastic order specifications, we formulate modeling for distributions ordered in variability. We work with Dirichlet process mixtures resulting in a fully Bayesian semiparametric approach. The details for simulation-based model fitting and prior specification are provided. An example, based on two small subsets of time intervals between eruptions of the Old Faithful geyser, illustrates the methodology.     

一种基于后验概率判决的one-by-one快速相关攻击算法(英文)

本文描述了一种基于后验概率判决的 one by one快速相关攻击算法.本文试图通过概率的观点来看待和分析快速相关攻击问题.该算法的优点有以下三点.首先,和文献[5]相比 one by one算法减少了对存储空间的需求.其次,提出了攻击失败概率的概念,并利用中心极限定理给出了它和密钥流序列长度的关系.最后,和文献[4]相比,该算法只需要更少的密钥流序列就可以达到几乎相同的攻击效果.     

Using probability trees to compute marginals with imprecise probabilities

This paper presents an approximate algorithm to obtain a posteriori intervals of probability, when available information is also given with intervals. The algorithm uses probability trees as a means of representing and computing with the convex sets of probabilities associated to the intervals.     

先验及后验概率下最优决策的选择

如何以最低代价获得最优决策方案是现代企业管理所面临的基本问题之一。在进行风险型决策过程中,若能结合抽样理论,就可以以最低的代价找到先验概率下及修正后的后验概率下选择最优决策方案。     

Residual Based a Posteriori Error Estimates for Convex Optimal Control Problems Governed by Stokes-Darcy Equations

In this paper, we derive a posteriori error estimates for finite element approximations of the optimal control problems governed by the Stokes-Darcy system. We obtain a posteriori error estimators for both the state and the control based on the residual of the finite element approximation. It is proved that the a posteriori error estimate provided in this paper is both reliable and efficient.     

A posteriori error analysis for a continuous space-time finite element method for a hyperbolic integro-differential equation

An integro-differential equation of hyperbolic type, with mixed boundary conditions, is considered. A continuous space-time finite element method of degree one is formulated. A posteriori error representations based on space-time cells is presented such that it can be used for adaptive strategies based on dual weighted residual methods. A posteriori error estimates based on weighted global projections and local projections are also proved.     

定常的Navier-Stokes方程的非线性Galerkin混合元法及其后验估计

提出了定常的Navier-Stokes方程的一种非线性Galerkin混合元法,并导出非线性Galerkin混合元解的存在性和误差估计及其后验误差估计.     

A posteriori error analysis of the discontinuous finite element methods for first order hyperbolic problems

In this paper, we consider the a posteriori error analysis of discontinuous Galerkin finite element methods for the steady and nonsteady first order hyperbolic problems with inflow boundary conditions. We establish several residual-based a posteriori error estimators which provide global upper bounds and a local lower bound on the error. Further, for nonsteady problem, we construct a fully discrete discontinuous finite element scheme and derive the a posteriori error estimators which yield global upper bound on the error in time and space. Our a posteriori error analysis is based on the mesh-dependent a priori estimates for the first order hyperbolic problems. These a posteriori error analysis results can be applied to develop the adaptive discontinuous finite element methods.