检索结果-南通市图书馆

On Stochastic Error and Computational Efficiency of the markov chain monte carlo method

Communications in Computational Physics 2014年第7期16卷 467-490页

作者： Jun Li Philippe Vignal Shuyu Sun Victor M.Calo Center for Numerical Porous Media King Abdullah University of Science and TechnologyThuwalSaudi Arabia Material Science and Engineering King Abdullah University of Science and TechnologyThuwalSaudi Arabia AppliedMathematics and Computational Science Earth Sciences and EngineeringKing Abdullah University of Science and TechnologyThuwalSaudi Arabia.

Inmarkov chainmonte carlo(MCMC)simulations,thermal equilibria quantities are estimated by ensemble average over a sample set containing a large number of correlated samples.These samples are selected in accordance with the probability distribution function,known from the partition function of equilibrium state.As the stochastic error of the simulation results is significant,it is desirable to understand the variance of the estimation by ensemble average,which depends on the sample size(i.e.,the total number of samples in the set)and the sampling interval(i.e.,cycle number between two consecutive samples).Although large sample sizes reduce the variance,they increase the computational cost of the simulation.For a given CPU time,the sample size can be reduced greatly by increasing the sampling interval,while having the corresponding increase in variance be negligible if the original sampling interval is very small.In this work,we report a few general rules that relate the variance with the sample size and the sampling interval.These results are observed and confirmed numerically.These variance rules are derived for theMCMCmethod but are also valid for the correlated samples obtained using other monte carlo methods.The main contribution of this work includes the theoretical proof of these numerical observations and the set of assumptions that lead to them.

关键词： Phase coexistence Gibbs ensemble molecular simulation markov chain monte carlo method variance estimation blocking method

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

The influence of ambient air pollution on the transmission of tuberculosis in Jiangsu,China

引用

Infectious Disease Modelling 2023年第2期8卷 390-402页

作者： Xiaomeng Wang Yongli Cai School of Mathematics and Statistics Huaiyin Normal UniversityHuaian223300PR China

In this paper,based on the statistical data,we investigate the effects of long-term exposure to ambient particulate air pollution on the transmission dynamics of tuberculosis(TB)in Jiangsu,China by studying the threshold dynamics of the TB epidemic model via the statistical data analytically and numerically.The basic reproduction number R_(0)>1 reveals that TB in Jiangsu,China is an endemic disease and will persist for a long time.And the numerical results show that,in order to control the TB in Jiangsu effectively,we must decrease the depuration coefficient of PM10 in the body,the proportion of TB symptomatic infectious by direct transmission,the reactivation rate of the pre-symptomatic infectious and the effect coefficient of PM10 and MTB inhaled of TB transmission,and increase the uptake coefficient,the recovery rate of the symptomatic/pre-symptomatic infectious and the influence coefficient of PM10 on the body of mortality.Our study shows that PM10 is closely related to the incidence of TB,and the effective control efforts are suggested to focus on increasing close-contact distance and wearing protective mask to decrease the influence of PM10 on the TB transmission,which may shed a new light on understanding the environmental drivers to TB.

关键词： Epidemic model Basic reproduction number Sensitivity analysis markov chain monte carlo method Control strategies

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Stochastic Volatility Modeling based on Doubly Truncated Cauchy Distribution and Bayesian Estimation for Chinese Stock Market

引用

应用数学学报:英文版 2023年第4期39卷 791-807页

作者： Cai-feng WANG Cong XIE Zi-yu MA Hui-min ZHAO School of Mathematics and Physics University of Science and Technology BeijingBeijing 100083China School of Business Sun Yat-sen UniversityGuangzhou 510275China

In order to measure the uncertainty of financial asset returns in the stock market, this paper presents a new model, called SV-dt C model, a stochastic volatility(SV) model assuming that the stock return has a doubly truncated Cauchy distribution, which takes into account the high peak and fat tail of the empirical distribution simultaneously. Under the Bayesian framework, a prior and posterior analysis for the parameters is made and markov chain monte carlo(MCMC) is used for computing the posterior estimates of the model parameters and forecasting in the empirical application of Shanghai Stock Exchange Composite Index(SSECI) with respect to the proposed SV-dt C model and two classic SV-N(SV model with Normal distribution)and SV-T(SV model with Student-t distribution) models. The empirical analysis shows that the proposed SV-dt C model has better performance by model checking, including independence test(Projection correlation test), Kolmogorov-Smirnov test(K-S test) and Q-Q plot. Additionally, deviance information criterion(DIC) also shows that the proposed model has a significant improvement in model fit over the others.

关键词： stochastic volatility model doubly truncated Cauchy distribution Bayesian estimation markov chain monte carlo method deviance information criterion

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A statistical inference for generalized Rayleigh model under Type-Ⅱ progressive censoring with binomial removals

引用

Journal of Systems Engineering and Electronics 2020年第1期31卷 206-223页

作者： REN Junru GUI Wenhao Department of Mathematics Beijing Jiaotong University

This paper considers the parameters and reliability characteristics estimation problem of the generalized Rayleigh distribution under progressively Type-Ⅱ censoring with random removals,that is,the number of units removed at each failure time follows the binomial distribution.The maximum likelihood estimation and the Bayesian estimation are derived.In the meanwhile,through a great quantity of monte carlo simulation experiments we have studied different hyperparameters as well as symmetric and asymmetric loss functions in the Bayesian estimation procedure.A real industrial case is presented to justify and illustrate the proposed methods.We also investigate the expected experimentation time and discuss the influence of the parameters on the termination point to complete the censoring test.

关键词： Type-Ⅱprogressive censoring with random removals generalized Rayleigh distribution reliability characteristic maximum likelihood estimation markov chain monte carlo method expected experimentation time

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：