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11.
BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE 总被引:1,自引:0,他引:1
Edward Cripps Robert Kohn David Nott 《Australian & New Zealand Journal of Statistics》2006,48(2):237-252
This article proposes a new data‐based prior distribution for the error variance in a Gaussian linear regression model, when the model is used for Bayesian variable selection and model averaging. For a given subset of variables in the model, this prior has a mode that is an unbiased estimator of the error variance but is suitably dispersed to make it uninformative relative to the marginal likelihood. The advantage of this empirical Bayes prior for the error variance is that it is centred and dispersed sensibly and avoids the arbitrary specification of hyperparameters. The performance of the new prior is compared to that of a prior proposed previously in the literature using several simulated examples and two loss functions. For each example our paper also reports results for the model that orthogonalizes the predictor variables before performing subset selection. A real example is also investigated. The empirical results suggest that for both the simulated and real data, the performance of the estimators based on the prior proposed in our article compares favourably with that of a prior used previously in the literature. 相似文献
12.
Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods 总被引:1,自引:0,他引:1
Alexander Morton Bärbel F. Finkenstädt 《Journal of the Royal Statistical Society. Series C, Applied statistics》2005,54(3):575-594
Summary. A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities. 相似文献
13.
黄善明 《扬州大学学报(人文社会科学版)》2004,8(3):31-36
新文学思潮与新文学流派之间因果莫辨、源流纠缠的动态关系 ,充分证明了近百年来新文学思潮与新文学流派本身非线性、非对称的生存状态。所谓非线性与非对称 ,其实质就是不稳定性和不成熟性 ,它们直接制约着新文学近百年发展进程 ,使之在历时态和共时态上始终呈现出某种程度的不良生存状态和发展趋势。 相似文献
14.
15.
In this paper we develop a study on several types of parallel genetic algorithms (PGAs). Our motivation is to bring some uniformity to the proposal, comparison, and knowledge exchange among the traditionally opposite kinds of serial and parallel GAs. We comparatively analyze the properties of steady-state, generational, and cellular genetic algorithms. Afterwards, this study is extended to consider a distributed model consisting in a ring of GA islands. The analyzed features are the time complexity, selection pressure, schema processing rates, efficacy in finding an optimum, efficiency, speedup, and resistance to scalability. Besides that, we briefly discuss how the migration policy affects the search. Also, some of the search properties of cellular GAs are investigated. The selected benchmark is a representative subset of problems containing real world difficulties. We often conclude that parallel GAs are numerically better and faster than equivalent sequential GAs. Our aim is to shed some light on the advantages and drawbacks of various sequential and parallel GAs to help researchers using them in the very diverse application fields of the evolutionary computation. 相似文献
16.
The HastingsMetropolis algorithm is a general MCMC method for sampling from a density known up to a constant. Geometric convergence of this algorithm has been proved under conditions relative to the instrumental (or proposal) distribution. We present an inhomogeneous HastingsMetropolis algorithm for which the proposal density approximates the target density, as the number of iterations increases. The proposal density at the n th step is a non-parametric estimate of the density of the algorithm, and uses an increasing number of i.i.d. copies of the Markov chain. The resulting algorithm converges (in n ) geometrically faster than a HastingsMetropolis algorithm with any fixed proposal distribution. The case of a strictly positive density with compact support is presented first, then an extension to more general densities is given. We conclude by proposing a practical way of implementation for the algorithm, and illustrate it over simulated examples. 相似文献
17.
Marco Bee 《Statistical Methods and Applications》2005,14(1):127-141
In this article we provide a rigorous treatment of one of the central statistical issues of credit risk management. GivenK-1 rating categories, the rating of a corporate bond over a certain horizon may either stay the same or change to one of the
remainingK-2 categories; in addition, it is usually the case that the rating of some bonds is withdrawn during the time interval considered
in the analysis. When estimating transition probabilities, we have thus to consider aK-th category, called withdrawal, which contains (partially) missing data. We show how maximum likelihood estimation can be
performed in this setup; whereas in discrete time our solution gives rigorous support to a solution often used in applications,
in continuous time the maximum likelihood estimator of the transition matrix computed by means of the EM algorithm represents
a significant improvement over existing methods. 相似文献
18.
Gaussian Markov random field (GMRF) models are commonly used to model spatial correlation in disease mapping applications. For Bayesian inference by MCMC, so far mainly single-site updating algorithms have been considered. However, convergence and mixing properties of such algorithms can be extremely poor due to strong dependencies of parameters in the posterior distribution. In this paper, we propose various block sampling algorithms in order to improve the MCMC performance. The methodology is rather general, allows for non-standard full conditionals, and can be applied in a modular fashion in a large number of different scenarios. For illustration we consider three different applications: two formulations for spatial modelling of a single disease (with and without additional unstructured parameters respectively), and one formulation for the joint analysis of two diseases. The results indicate that the largest benefits are obtained if parameters and the corresponding hyperparameter are updated jointly in one large block. Implementation of such block algorithms is relatively easy using methods for fast sampling of Gaussian Markov random fields ( Rue, 2001 ). By comparison, Monte Carlo estimates based on single-site updating can be rather misleading, even for very long runs. Our results may have wider relevance for efficient MCMC simulation in hierarchical models with Markov random field components. 相似文献
19.
供应链企业间的合作轨道模型 总被引:3,自引:0,他引:3
文章主要介绍了轨道模型在供应链企业合作中的应用 ,根据合作程度的不同 ,伙伴企业处于以核心企业为中心的不同轨道。文章分别从静态和动态的角度运用轨道模型分析了企业间合作关系以及这种合作关系的变化。一方面使企业间的合作问题简单化 ;另一方面 ,轨道模型便于对合作问题进行深入的定量化研究。 相似文献
20.
基于需求不确定性的供应链库存控制研究 总被引:3,自引:0,他引:3
潘文安 《武汉理工大学学报(社会科学版)》2004,17(6):698-702
通过建立需求不确定性环境下供应链成员的独立存货成本模型,运用模拟退火法对该模型进行52周的仿真,求解存货最佳订购数量与最佳再订购点,从而比较出不同存货控制策略的供应链存货总成本及订单满足率的差异。 相似文献