不完备广义多尺度决策系统的逐步最优尺度选择

现有的最优尺度选择算法有可能无法得到全局最优尺度组合,且具有较高的时间和空间复杂度。针对该问题,提出了不完备广义多尺度决策系统的逐步最优尺度选择算法。介绍了不完备广义多尺度决策系统,给出了上下近似集的性质;采取属性约简与尺度选择同步优化策略,以得到全局最优尺度组合;给出了一个快速的求相容类方法,并提出了不完备广义多尺度决策系统的逐步最优尺度组合选择算法,该算法显著降低了时间复杂度与空间复杂度。数值实验表明所提出的算法是有效的。     

基于凸组合技术的加速FR型共轭梯度算法

为高效求解非线性方程组问题,利用凸组合技术设计一个新型搜索方向,同时结合加速线搜索技术,提出一个新的加速FR型共轭梯度算法.在合理的假设下,新算法拥有全局收敛的良好性质.数值试验结果表明,新算法总体上优于经典FR算法和三项FR算法.新算法继承了修正FR方法的良好数值效果、充分下降性及信赖域特征,并具有计算简单和存储量小...     

系统非线性组合预测方法及在黄河凌汛预测中应用

为了提高预测的精度,尤其是冰凌中长期预测的精度,基于工程模糊集、人工神经网络、遗传算法与组合预测理论,提出了系统非线性组合预测方法,给出了黄河内蒙段冰凌三种单一预测模型的非线性组合预测值．结果表明,所建立的非线性组合预测方法物理意义明确,数学推导过程严谨,预测精度高于任意单一预测模型．     

证券投资组合的解析算法

给出了证券组合模型, 在其使对称矩阵与对角矩阵合同的可逆阵的一般规律基础上, 推导出证券投资组合给合权数的解析表达式, 并给出实例验证.     

Does a lot help a lot? Forecasting stock returns with pooling strategies in a data‐rich environment

A variety of recent studies provide a skeptical view on the predictability of stock returns. Empirical evidence shows that most prediction models suffer from a loss of information, model uncertainty, and structural instability by relying on low‐dimensional information sets. In this study, we evaluate the predictive ability of various lately refined forecasting strategies, which handle these issues by incorporating information from many potential predictor variables simultaneously. We investigate whether forecasting strategies that (i) combine information and (ii) combine individual forecasts are useful to predict US stock returns, that is, the market excess return, size, value, and the momentum premium. Our results show that methods combining information have remarkable in‐sample predictive ability. However, the out‐of‐sample performance suffers from highly volatile forecast errors. Forecast combinations face a better bias–efficiency trade‐off, yielding a consistently superior forecast performance for the market excess return and the size premium even after the 1970s.     

Forecast Combination and Bayesian Model Averaging: A Prior Sensitivity Analysis

In this study we evaluate the forecast performance of model‐averaged forecasts based on the predictive likelihood carrying out a prior sensitivity analysis regarding Zellner's g prior. The main results are fourfold. First, the predictive likelihood does always better than the traditionally employed ‘marginal’ likelihood in settings where the true model is not part of the model space. Secondly, forecast accuracy as measured by the root mean square error (RMSE) is maximized for the median probability model. On the other hand, model averaging excels in predicting direction of changes. Lastly, g should be set according to Laud and Ibrahim (1995: Predictive model selection. Journal of the Royal Statistical Society B 57 : 247–262) with a hold‐out sample size of 25% to minimize the RMSE (median model) and 75% to optimize direction of change forecasts (model averaging). We finally apply the aforementioned recommendations to forecast the monthly industrial production output of six countries, beating for almost all countries the AR(1) benchmark model. Copyright © 2011 John Wiley & Sons, Ltd.     

A study of Platyplectrus Ferrière (Hymenoptera: Eulophidae) in mainland China

This paper reviews the Chinese species of Platyplectrus Ferrière. Twelve valid species are recognized from mainland China and a key to species is provided. Trichoplectrus Erdös (1951 Erdös, J, 1951. "Eulophidae novae. Acta Biologica". 1951, Academiae Scientiarum Hungaricae, 2(1–3), 169–237. [Google Scholar]) is newly synonymized with Metaplectrus Ferrière (1941 Ferrière, C, 1941. New species of Euplectrini (Hym. Chalcidoidea) from Europe, Africa and Asia, Bulletin of Entomological Research 32 (1941), pp. 17–48.[Crossref] , [Google Scholar]) and three new combinations are proposed: Metaplectrus szepligetii (Erdös) from Platyplectrus, Platyplectrus bussy (Crawford) from Euplectrus and P. politus (Lin) from Metaplectrus. Four species of Platyplectrus were known previously from China: P. politus (Lin), P. odontogaster (Lin), P. papillata Lin and P. medius Zhu and Huang. Six species, P. bussyi (Crawford), P. laeviscuta (Thomson), P. natadae Ferrière, P. orthocraspedae Ferrière, P. pannonica (Erdös) and P. viridiceps (Ferrière) are newly recorded from China and re-described. Five new species, P. pulcher, P. setulosus, P. peculiaris, P. obtusiclavatus and P. variflagellum are described and compared with related species. Several species are also newly recorded from other regions: P. orthocraspedae Ferrière from the Afrotropical region, P. bussyi (Crawford) and P. laeviscuta (Thomson) from the Australian/Pacific region, P. laeviscuta (Thomson) from the Oriental region and P. viridiceps from the Palearctic region.     

Revision of the genus Mimopodabrus Wittmer (Coleoptera,Cantharidae)

The genus Mimopodabrus Wittmer is reviewed, and the genus diagnosis is re-described. Three new species are described, M. multidentatus sp. nov. (Guangdong, China), M. variabilis sp. nov. (Yunnan, China) and M. diversefoveolatus sp. nov. (Lao Cai, Vietnam), with illustrations of habitus, antennae and aedeagus. A species is transferred from Micropodabrus to this genus, M. bicoloriceps (Wittmer, 1989 Wittmer, W. 1989. 42. Beitrag zur Kenntnis der indo-malaiischen Cantharidae und Malachiidae (Coleoptera). Entomol Basil., 13: 209–237.  [Google Scholar]) comb. nov. A species is synonymized, M. bicoloriceps (Wittmer, 1989 Wittmer, W. 1989. 42. Beitrag zur Kenntnis der indo-malaiischen Cantharidae und Malachiidae (Coleoptera). Entomol Basil., 13: 209–237.  [Google Scholar]) comb. nov.?=?M. bicoloriceps Wittmer, 1997 syn. nov. and the definition of M. yunnanus (Wittmer, 1993 Wittmer, W. 1993. Zur Kenntnis der palaearktischen und indo-malaiischen Cantharidae (Coleoptera). Entomol Basil., 16: 203–253.  [Google Scholar]) is restricted. A key to all known species of this genus is provided.     

供应链产品质量检查策略的比较研究

研究由一个供应商和一个零售商组成的供应链,建立存在质量不确定与检查错误下的报童模型,比较分析全检、抽检、分批抽检以及组合策略在分散式与集中式供应链中对零售商订购决策与质量控制效率的影响.结果表明,次品率的增加会降低零售商订购产品的动因,但会增加组合策略下零售商的订购量与利润,同时对集中式供应链中全检策略下的零售商有利;比较策略可知,在分散式供应链中,若次品率较低,则分批抽检策略最优,而随着次品率的提高,组合策略会更优,而在集中式供应链中,全检策略最优;此外零售商质量控制策略的选择受到检查精度、责任成本、次品率阈值、抽检数量以及分批次数等诸多因素的影响,最优策略不尽相同,但不会改变零售商利润随次品率变化的趋势.     

The impact of parameter and model uncertainty on market risk predictions from GARCH‐type models

We study the effect of parameter and model uncertainty on the left‐tail of predictive densities and in particular on VaR forecasts. To this end, we evaluate the predictive performance of several GARCH‐type models estimated via Bayesian and maximum likelihood techniques. In addition to individual models, several combination methods are considered, such as Bayesian model averaging and (censored) optimal pooling for linear, log or beta linear pools. Daily returns for a set of stock market indexes are predicted over about 13 years from the early 2000s. We find that Bayesian predictive densities improve the VaR backtest at the 1% risk level for single models and for linear and log pools. We also find that the robust VaR backtest exhibited by linear and log pools is better than the backtest of single models at the 5% risk level. Finally, the equally weighted linear pool of Bayesian predictives tends to be the best VaR forecaster in a set of 42 forecasting techniques.