贝叶斯推断与资产组合有效性检验

本文认为,资产组合P的均值-方差有效性能够通过有效性指标ρ的后验分布获得。根据贝叶斯法则,我们选取上证综合指数为样本获得了ρ的后验分布。研究结论表明,如果资产组合集中包含有无风险资产,当先验信仰以标准无信息先验(标准扩散先验)的形式出现时,上证综合指数缺乏有效性,表明资产组合集中加入无风险资产将降低资产组合的均值-方差有效性,这与理论推导结果是一致的。     

Bayesian inference and prediction in the single server Markovian queue

The use of stochastic models and performance measures for the analysis of real life queuing scenarios are based on the fundamental premise that parameters values are known. This is a rarity since more often than not, parameters are usually unknown and require to be estimated. This paper presents techniques for the same from Bayesian perspective. The queue we intend to deal with is the M/M/1 queuing model. Several closed form expressions on posterior inference and prediction are presented which can be readily implemented using standard spreadsheet tools. Previous work in this direction resulted in non-existence of posterior moments. A way out is suggested. Interval estimates and tests of hypothesis on performance measures are also presented.     

Forecasting an accumulated series based on partial accumulation II: A new Bayesian method for short series with stable seasonal patterns

The problem of forecasting a time series with only a small amount of data is addressed within a Bayesian framework. The quantity to be predicted is the accumulated value of a positive and continuous variable for which partially accumulated data are available. These conditions appear in a natural way in many situations. A simple model is proposed to describe the relationship between the partial and total values of the variable to be forecasted assuming stable seasonality, which is specified in stochastic terms. Analytical results are obtained for both the point forecast and the entire posterior predictive distribution. The proposed technique does not involve approximations. It allows the use of non-informative priors so that implementation may be automatic. The procedure works well when standard methods cannot be applied due to the reduced number of observations. It also improves on previous results published by the authors. Some real examples are included.     

Bayesian modeling of joint and conditional distributions

In this paper, we study a Bayesian approach to flexible modeling of conditional distributions. The approach uses a flexible model for the joint distribution of the dependent and independent variables and then extracts the conditional distributions of interest from the estimated joint distribution. We use a finite mixture of multivariate normals (FMMN) to estimate the joint distribution. The conditional distributions can then be assessed analytically or through simulations. The discrete variables are handled through the use of latent variables. The estimation procedure employs an MCMC algorithm. We provide a characterization of the Kullback–Leibler closure of FMMN and show that the joint and conditional predictive densities implied by the FMMN model are consistent estimators for a large class of data generating processes with continuous and discrete observables. The method can be used as a robust regression model with discrete and continuous dependent and independent variables and as a Bayesian alternative to semi- and non-parametric models such as quantile and kernel regression. In experiments, the method compares favorably with classical nonparametric and alternative Bayesian methods.     

On randomization, modeling and experimental design; a new example in an old discussion

Fisher and "Student" quarreled in the early days of statistics about the design of experiments, meant to measure the difference in yield between to breeds of corn. This discussion comes down to randomization versus model building. More than half a century has passed since, but the different views remain. In this paper the discussion is put in terms of artificial randomization and natural randomization, the latter being what remains after appropriate modeling. Also the Bayesian position is discussed. An example in terms of the old corn-breeding discussion is given, showing that a simple robust model may lead to inference and experimental design that outperforms the inference from randomized experiments by far. Finally similar possibilities are suggested in statistical auditing.     

咸宁温泉酒店生态足迹分析

本文运用生态足迹法作为咸宁市温泉酒店环境影响评估工具,以进一步了解温泉酒店本身对资源的运用与效率。对市内4家温泉酒店调查及计算,结果显示皆以C温泉酒店的生态足迹最小,显示出其在单位面积、能源及水资源使用上有较好的效率。整体而言,想要减少温泉酒店的生态足迹,应着眼于加强酒店利用再生能源与提高能源使用效率。     

Empirical factor demands and flexible functional forms: a bayesian approach

In this paper we compare classical econometrics, calibration and Bayesian inference in the context of the empirical analysis of factor demands. Our application is based on a popular flexible functional form for the firm's cost function, namely Diewert's Generalized Leontief function, and uses the well-known Berndt and Wood 1947–1971 KLEM data on the US manufacturing sector. We illustrate how the Gibbs sampling methodology can be easily used to calibrate parameter values and elasticities on the basis of previous knowledge from alternative studies on the same data, but with different functional forms. We rely on a system of mixed non-informative diffuse priors for some key parameters and informative tight priors for others. Within the Gibbs sampler, we employ rejection sampling to incorporate parameter restrictions, which are suggested by economic theory but in general rejected by economic data. Our results show that values of those parameters that relate to non-informative priors are almost equal to the standard SUR estimates, whereas differences come out for those parameters to which we have assigned informative priors. Moreover, discrepancies can be appreciated in some crucial parameter estimates obtained with or without rejection sampling.     

Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures

Abstract.  In this paper, we review and unite the literatures on returns to schooling and Bayesian model averaging. We observe that most studies seeking to estimate the returns to education have done so using particular (and often different across researchers) model specifications. Given this, we review Bayesian methods which formally account for uncertainty in the specification of the model itself, and apply these techniques to estimate the economic return to a college education. The approach described in this paper enables us to determine those model specifications which are most favored by the given data, and also enables us to use the predictions obtained from all of the competing regression models to estimate the returns to schooling. The reported precision of such estimates also account for the uncertainty inherent in the model specification. Using U.S. data from the National Longitudinal Survey of Youth (NLSY), we also revisit several 'stylized facts' in the returns to education literature and examine if they continue to hold after formally accounting for model uncertainty.     

城市园林绿地的生态效益

从生态学角度论述了城市园林绿地的生态效益,论证了绿色植物对城市环境的重要性.     

城市湿地的生态功能

城市湿地是城市重要的生态基础设施 ,是城市可持续发展依赖的重要自然系统 ,具有众多的生态及社会服务功能。城市发展过程中的不合理开发往往导致湿地功能的退化 ,为达到城市湿地的可持续利用目的 ,必须采取相应的治理措施。     

生态城市与生态产业链——以芜湖市为例

阐述了生态城市的内涵,结合芜湖生态市规划实践,在探讨芜湖市产业结构演变与特点的基础上,以生态机制为理论背景,按照循环经济模式,对芜湖市生态产业链进行设计,其中包括五条生态工业链、三条生态农业链。并对生态产业布局、产业与产业链之间的联系以及生态产业链的设计思想进行了初步探索。     

河道管理存在的问题及生态治理建议

在工业化发展迅速的今天,我国经济不断增长的同时,人们对于水资源的需求度也在不断提高,然而城市可用水的破坏程度也在发展的同时得到破坏,引发现阶段人类和河道共同争水的现象。因此,要想解决这一问题,就必须加强对河道的管理,找出河道管理中存在的不足并加以解决,最终实现生态建设发展。     

生态景观公园规划设计——玉湖公园规划设计探析

施甸县的玉湖公园作为展示施甸县形象的窗口,从城市公园园林植物造景的角度,结合园林建筑、园路和景点的土建规划设计对其现有绿化进行改造。文章基于笔者实际工作经验,根据规划的指导思想与规划理念,对公园绿化规划设计作了详细的分析。     

The demand for judicial sanctions: voter information and the election of judges

We examine 20 partisan judicial elections over an 8-year period to determine whether judge specific information shows in election results. We find demand for judicial sanctions looks much like other voting processes. Among voters, Democratic incumbent judges, who tend to be lenient, are rewarded for being harsh, while Republican incumbent judges, who generally are harsh, are rewarded for being lenient. Voters are not found to be a random sample of the population, and we find that straight ticket votes obscure information from selective voters. This paper benefitted from comments received by participants at the Public Choice Meetings, and from useful comments from Aimee Chin, Janet Kohlhase, an anonymous referee and the editor.     

实现绿色崛起——打造洞庭湖生态经济区的必由之路

洞庭湖区是湖南省的"鱼米之乡",对湖南经济社会的发展具有十分重要的战略意义,"十五"规划以来,洞庭湖区域经济迅速发展,但受特殊人、地、水关系和其他各种因素的影响,区内仍存在着区域协调发展不合理,水资源匮乏和环境污染严重等问题,因此,合理规划湖区生态经济区,对调整洞庭湖生态经济区的产业结构和经济发展方向,促进区内经济与环境保护协调发展,实现人地协调共生有着重大意义。     

我国生态文明建设的重要意义及实现路径

建设生态文明,是走向社会主义新时代的必然要求。推进生态文明建设,可以最大限度地沉淀绿色发展沃土,铸就天蓝、地绿、水清的美丽家园,描绘出生态“高颜值”、发展“好气质”、经济“稳进好”的魅力中国画卷。推进生态文明建设,可进一步落实良好民生,为开创我国良好生态环境的新起点、新局面、新征程夯实根基。     

旅游循环经济与乡村生态旅游的耦合——以珠江源风景区为例

针对珠江源风景区及周边乡村的现状,根据旅游循环经济和乡村生态旅游资源循环利用和保护并重的理念,分析了在珠江源周边的二道沟村、青山村、刘麦地村发展乡村生态旅游的可行性,提出基于循环经济三原则的乡村生态旅游发展,以促进珠江源风景区的健康可持续发展,促进周边乡村经济发展、新农村建设和产业结构转型。     

The emperor's new clothes: a critique of the multivariate t regression model

Zellner (1976) proposed a regression model in which the data vector (or the error vector) is represented as a realization from the multivariate Student t distribution. This model has attracted considerable attention because it seems to broaden the usual Gaussian assumption to allow for heavier-tailed error distributions. A number of results in the literature indicate that the standard inference procedures for the Gaussian model remain appropriate under the broader distributional assumption, leading to claims of robustness of the standard methods. We show that, although mathematically the two models are different, for purposes of statistical inference they are indistinguishable. The empirical implications of the multivariate t model are precisely the same as those of the Gaussian model. Hence the suggestion of a broader distributional representation of the data is spurious, and the claims of robustness are misleading. These conclusions are reached from both frequentist and Bayesian perspectives.     

生态文明视角下旅游物流绿色发展实施路径研究

从生态文明视角提出了绿色旅游物流的概念并对其内涵进行了剖析,进而分析了旅游物流绿色发展的重要意义和面临的问题,最后探讨了通过理念革新、现代营销、先进技术和专业人才等措施,促进旅游物流绿色发展的具体路径。     

Information loss for 2 × 2 tables with missing cell counts: binomial case

We formulate likelihood-based ecological inference for 2 × 2 tables with missing cell counts as an incomplete data problem and study Fisher information loss by comparing estimation from complete and incomplete data. In so doing, we consider maximum-likelihood (ML) estimators of probabilities governed by two independent binomial distributions and obtain simplified expressions for their covariance. These expressions reflect well the additional uncertainty arising from the unobserved data compared to complete data tables. We also discuss an approximation to the expected conditional variance of the unobserved entries and ML parameter bias correction. An empirical example is used to demonstrate the results.