共查询到20条相似文献，搜索用时 218 毫秒
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在非对称损失函数-GE损失函数下,利用非参数核密度估计方法,构造了单边截断型分布族未知参数的经验Bayes(EB)估计,并在适当条件下,证明了它的收敛速度,最后,给出了一个例子说明适合定理条件的先验分布是存在的. 相似文献
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贝叶斯方法是对多项分布参数进行点估计的重要方法.在统计学家对无信息先验作了大量的研究工作的基础上,通过推导得到一组关于该无信息先验分布的结论并利用这组结论研究其后验均值.结果表明:后验均值可使后验均方差达到最小. 相似文献
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目的:碾压混凝土坝施工过程中施工仿真参数会随着施工现场环境变化而变化。本文探讨实时监控方法获取的施工信息对施工进度仿真的影响,研究碾压混凝土坝施工仿真参数自适应更新方法,提高施工仿真的精度。创新点:1.通过碾压混凝土坝施工信息实时获取技术,分析计算碾压混凝土坝施工仿真参数;2.利用贝叶斯更新技术对施工仿真参数进行更新;3.利用模糊均生函数对坝区短期降雨量进行预测;4.建立基于实时监控的碾压混凝土坝施工仿真模型,对碾压混凝土坝施工过程进行仿真并与实际施工进度对比。方法:1.通过实地采集,获取碾压混凝土坝施工过程中实时施工信息(图2);2.通过理论推导,构建施工仿真参数先验分布均值和方差与后验分布均值和方差之间的关系,得到施工仿真参数更新方案(公式(16)和(17));3.通过理论推导,利用已知坝区降雨量数据预测未来短期内的降雨情况(图5);4.通过仿真模拟,得到施工仿真参数更新后的仿真成果并将其与实际施工进行对比,验证本方法的有效性和准确性。结论:1.施工仿真参数的准确性对碾压混凝土坝施工仿真结果准确性有很大影响;2.可以利用贝叶斯更新技术对施工仿真中的仿真参数进行更新,利用模糊均生函数对坝区短时期内降雨量进行预测;3.运用基于实时监控的碾压混凝土坝施工仿真方法对碾压混凝土坝施工过程进行仿真,仿真结果与实际施工进度之间的偏差明显减少,仿真准确性明显提高。 相似文献
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为了求解参数估计中的统计推断问题,将不含参数的非参数核密度估计和经验分布函数作为"理论分布",含参数的密度函数和分布函数作为"拟合分布",逆向地将实际中的两类分布角色互换,然后构建拟合分布与理论分布偏差的目标函数。再基于优化理论得到使得目标函数达到最小的参数值作为未知参数的估计,由此构建了求解经典的参数推断问题的两种逆向求解法。通过柯西分布参数的随机模拟试验,说明了逆向法的可行性和普适性;再结合Bootstrap方法,对常见分布参数的区间估计和检验p值进行随机模拟。结果表明,逆向方法在上述参数统计推断问题上的可行性;基于分布函数的逆向法优于基于密度函数的逆向法。 相似文献
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文中证明了泊松分布中未知参数的矩估计和最大似然估计,一定存在一个先验分布,使其贝叶斯估计就是该经典估计的结论. 相似文献
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在双边定数截尾样本下讨论了线性指数分布中未知参数的极大似然估计和Bayes估计.通过Newton-Raphson迭代法得到了参数的极大似然估计,并证明了极大似然估计的唯一存在性.选取无信息先验分布与共轭先验分布,分别在对称损失函数和非对称损失函数下,通过Tierney-Kadane近似讨论参数的Bayes近似估计.利用MatlabR200b模拟了未知参数的极大似然估计的均方误差以及Bayes估计的均方误差,结果表明：不同样本量不同截尾方案下,选取Gamma先验分布并在平方损失函数下,未知参数的Bayes估计的均方误差是最小的. 相似文献
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Bootstrap方法(也称自助法)是非参数统计中一种非常重要的统计方法.这种方法是将从样本中抽样得到的子样本看作样本,每一次抽出子样本后,计算一次统计量的观测值.通过反复抽样,可得到许多的统计量观测值.进一步可获得统计量的经验分布,然后进行统计推断.并举例说明了在Bootstrap方法下均值与方差的区间估计以及Bootstrap方法的均值的假设检验. 相似文献
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考虑非参数方差模型Yi=σ(xi)εi,i=1,2,…,n,其中xi是固定设计点列,{εi}是严平稳α-混合序列.该文利用小波方法构造了方差函数σ2(x)的估计量,在设定的假设条件下,讨论了其小波估计的有偏性、方差和相合性. 相似文献
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In psychological, social, behavioral, and medical studies, hidden Markov models (HMMs) have been extensively applied to the simultaneous modeling of heterogeneous observation and hidden transition in the analysis of longitudinal data. However, the majority of the existing HMMs are developed in a parametric framework without latent variables. This study considers a novel semiparametric HMM, which comprises a semiparametric latent variable model to investigate the complex interrelationships among latent variables and a nonparametric transition model to examine the linear and nonlinear effects of potential predictors on hidden transition. The Bayesian P-splines approach and Markov chain Monte Carlo methods are developed to estimate the unknown, a Bayesian model comparison statistic, is employed to conduct model comparison. The empirical performance of the proposed methodology is evaluated through simulation studies. An application to a data set derived from the National Longitudinal Survey of Youth is presented. 相似文献
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马尔可夫预测方法在预测领域有着广泛的应用．该方法应用的一个重要的问题就是如何估计一步状态转移概率矩阵．在历史资料没有给出系统处于n个状态次数的情况下，给出一步状态转移概率矩阵估计的最优化方法．最后探讨了基于Markov链的最优化预测模型在长江水质预测中的应用，从而表明该模型的有效性． 相似文献
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在混合模型的观点下,状态转移模型形成具有后验权重的混合模型,它通过后验概率推测分布来源,再结合Markov转移概率矩阵实现对分布持续性的刻画,从而弥补固定权重混合模型在时变性和相关性方面的缺陷.文章得到了该模型下随机变量的条件分布和无条件分布的递推式,从而得到条件与无条件期望、方差,进一步研究了平稳性条件,揭示了模型二阶矩的相关性.最后通过实例展示了Markov后验权重混合模型的优越性和对"波动聚集"的捕捉能力. 相似文献
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Hefei Liu 《Structural equation modeling》2018,25(1):41-55
Multivariate heterogenous data with latent variables are common in many fields such as biological, medical, behavioral, and social-psychological sciences. Mixture structural equation models are multivariate techniques used to examine heterogeneous interrelationships among latent variables. In the analysis of mixture models, determination of the number of mixture components is always an important and challenging issue. This article aims to develop a full Bayesian approach with the use of reversible jump Markov chain Monte Carlo method to analyze mixture structural equation models with an unknown number of components. The proposed procedure can simultaneously and efficiently select the number of mixture components and conduct parameter estimation. Simulation studies show the satisfactory empirical performance of the method. The proposed method is applied to study risk factors of osteoporotic fractures in older people. 相似文献
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Most of the software that is available to implement Bayesian approaches uses Markov chain Monte Carlo (MCMC) methods. It is our impression that many researchers are primarily concerned with convergence as assessed by the Potential Scale Reduction (PSR) and that other aspects of MCMC are largely ignored. In this article, we argue that the precision with which the Bayesian estimates are approximated by summary statistics for the MCMC chain is essential to ensure good statistical properties. We discuss the Effective Sample Size (ESS), which indicates how well an estimate is approximated, and present evidence from two simulation studies and an example from organizational research to support our claim that researchers should be concerned not only with convergence but also with precision, particularly when a multilevel model is estimated. In addition, we demonstrate how Mplus can be modified so that users can control the ESS, and we conclude with recommendations. 相似文献
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针对工业生产过程中的时变性问题,提出贝叶斯网络框架下的自适应质量变量预测建模方法。采用改进的即时学习策略,将数据库分成若干局部数据子集,快速选择与待测样本相似度较高的一组数据作为训练样本, 再利用主成分分析对训练样本过程变量进行特征提取,借此作为网络模型输入变量。利用基于改进Figueiredo-Jain算法的EM算法估计高斯混合模型参数,构建高斯混合模型逼近贝叶斯网络联合概率密度,训练得到贝叶斯网络下的自适应质量变量预测模型。基于田纳西伊斯曼（TE）仿真过程获得的数据,利用该方法对成分XG进行预测并与传统PCA-BN模型对比。结果证实该方法最大误差下降14.4%,均方根误差下降7.5%,相对误差下降8.3%,验证了该方法解决时变性问题的有效性。 相似文献
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This paper deals with the statistical modeling of latent topic hierarchies in text corpora. The height of the topic tree is assumed as fixed, while the number of topics on each level as unknown a priori and to be inferred from data. Taking a nonparametric Bayesian approach to this problem, we propose a new probabilistic generative model based on the nested hierarchical Dirichlet process （nHDP） and present a Markov chain Monte Carlo sampling algorithm for the inference of the topic tree structure as well as the word distribution of each topic and topic distribution of each document. Our theoretical analysis and experiment results show that this model can produce a more compact hierarchical topic structure and captures more fine-grained topic relationships compared to the hierarchical latent Dirichlet allocation model. 相似文献
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Naoya Todo 《Structural equation modeling》2016,23(5):695-712
In longitudinal design, investigating interindividual differences of intraindividual changes enables researchers to better understand the potential variety of development and growth. Although latent growth curve mixture models have been widely used, unstructured finite mixture models (uFMMs) are also useful as a preliminary tool and are expected to be more robust in identifying classes under the influence of possible model misspecifications, which are very common in actual practice. In this study, large-scale simulations were performed in which various normal uFMMs and nonnormal uFMMs were fit to evaluate their utility and the performance of each model selection procedure for estimating the number of classes in longitudinal designs. Results show that normal uFMMs assuming invariance of variance–covariance structures among classes perform better on average. Among model selection procedures, the Calinski–Harabasz statistic, which has a nonparametric nature, performed better on average than information criteria, including the Bayesian information criterion. 相似文献
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马尔可夫预测法是应用概率论中马尔可夫链的理论和方法来研究各种状态的变化规律,并由此预测状态未来变化趋势的一种方法。农村劳动力的流动受到多种因素影响,可以看作是一个随机的状态过程。马尔可夫链是对农村劳动力的流动预测的一个较好的方法,本文利用马尔可夫链对永兴傣族乡农村劳动力流动趋势进行了预测分析。 相似文献