Search for the upper bound of Bayesian estimates of the parameter in an exponential failure model with two known quantiles of an a priori distribution function

A fast exact algorithm of searching for the upper bound of Bayesian estimates for the parameter of the exponential distribution under the condition that an a priori distribution belongs to the class of all distribution functions with two equal quantiles. This problem arises in analyzing the sensitivity of Bayesian estimates to the choice of an a priori distribution in an exponential failure model. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 1, pp. 90–102, January–February 2007.     

基于VMD与改进QRGRU的超短期风电功率概率预测

风电功率概率预测是分析未来风电功率不确定性的有效方法之一。为提高风电功率概率预测精度,文中提出基于变分模态分解(VMD)与改进门控循环单元分位数回归(QRGRU)的超短期风电功率概率预测方法。首先,采用VMD将原始风电功率序列分解成不同特征的模态函数;然后,对每个模态函数分别建立基于QRGRU的概率预测模型,并将变量间的网络结构约束作为目标函数的惩罚项,改进QRGRU权重在迭代修正过程中的平稳性;最后,在不同分位数条件下叠加各个模态函数预测值,并采用非参数核密度估计方法得到未来风电功率的概率密度函数。结合某风电场实测数据开展具体算例分析,结果表明所提方法能够兼顾区间覆盖率,减少区间宽度,在不同预测步长中均能表现较好的预测效果。     

基于增量动力分析的重力坝抗震性能评估

基于增量动力分析法(IDA),采用塑性耗能与总变形能的比值作为结构性能指标,提出了重力坝抗震性能评价的三级震害划分和两个极限状态下的失效性划分的建议,做出IDA曲线,并结合分位数分析和易损性分析对重力坝抗震性能进行评估。以邯郸京娘湖重力坝为例,进行一系列的非线性分析,结果表明:分位数分析的IDA曲线中每个极限状态的峰值地面加速度PGA均大于设计地震的峰值地面加速度,满足该重力坝的功能保障性水平和安全保证性水平。易损性分析下,1.5倍设计地震作用时65.92%的概率处于正常使用阶段,100%可以保证安全。结果表明该重力坝具有良好的抗震性能。该项研究结果为重力坝抗震性能设计和安全风险评估提供了新思路。     

Development of Habitat Suitability Criteria and In‐Stream Habitat Assessment for the Benthic Cyanobacteria Phormidium

Global demand for freshwater has led to unprecedented levels of water abstraction from riverine systems. This has resulted in large alterations in natural river flows. The deleterious impacts of reduced flows on fish and macroinvertebrate abundances have been thoroughly investigated; in contrast, there is a limited understanding of the potential for changes in the abundance of nuisance benthic algal/cyanobacterial blooms. In New Zealand, Phormidium sp. blooms are common in numerous rivers during summer low flows. In this study, an in‐stream habitat assessment is used to examine the relationship between Phormidium habitat availability and reducing flows. Over 650 observations of Phormidium mats, from seven sites (Hutt River, lower North Island, New Zealand), were used to construct habitat suitability curves for depth, velocity and substrate. Preference curves were fitted using both the ‘forage ratio’ and ‘quantile regression’ methods. Phormidium growth, observed at all seven sites, increased significantly from upstream (uppermost site, 5.2% mat cover) to downstream (63.5%). The habitat suitability curves revealed Phormidium had a large tolerance to velocity, depth and substrate type. Consequently, decreases in flow had only negligible effects on available Phormidium habitat. During periods of stable flow, Phormidium abundance positively correlated with increased nitrogen concentrations, potentially explaining the large variation in Phormidium cover from upstream to downstream. Quantile regression generated habitat suitability criteria were a more accurate predictor of available Phormidium habitat than the forage ratio criteria. Copyright © 2013 John Wiley & Sons, Ltd.     

数据流上的分位数近似算法研究

数据流是一种新型数据模型,广泛应用于交通流量监控、通信管理、传感器网络、股票分析、Web点击流等众多领域.近年来越来越多的学者关注于数据流上的分位数计算研究.由于流数据的连续、无界、易失等特性,存储完整的流数据信息并得到精确的查询结果几乎是不可能的.在实施查询计算时追求内存用量与查询精度之间的最佳均衡.设计了规范数直方图的概要数据结构以存储流数据的摘要信息,并在此基础上提出了单遍扫描的、联机的分位数近似算法,其时间和空间复杂度均线性于概要结构中桶的个数,而与数据流的长度无关,因而具有很好的可规模性.该方法在均匀分布的数据上取得了优良性能.分析了算法精度与内存需求的关系.实验结果表明该算法具有较精确的查询结果,具备良好的实用性和有效性.     

Model selection in binary and tobit quantile regression using the Gibbs sampler

A stochastic search variable selection approach is proposed for Bayesian model selection in binary and tobit quantile regression. A simple and efficient Gibbs sampling algorithm was developed for posterior inference using a location-scale mixture representation of the asymmetric Laplace distribution. The proposed approach is then illustrated via five simulated examples and two real data sets. Results show that the proposed method performs very well under a variety of scenarios, such as the presence of a moderately large number of covariates, collinearity and heterogeneity.     

Mapping average equivalized income using robust small area methods

Measures of economic well‐being are often needed for geographically small areas, as economic indicators may be distributed unevenly among the subsets of relatively small regions. We consider small area estimation of average equivalized income. Disposable household income data are usually available only for a sample of households, typically too small to provide reliable estimates for small regions. We consider a small area estimation technique that is robust to outliers, produces results consistent with design weighted estimates obtained for larger areas and yield maps with approximately no shrinkage. The proposed methodology is applied to the Local Labour Systems in Tuscany (Italy).     

The value of quality clues in the wine market: evidences from Lazio,Italy

The purpose of the paper is to contribute to understanding the role and effectiveness of different quality clues in the creation of value for the main wines of the Lazio region. The study presents a hedonic price model. An ordinary least squares and a quantile regression models were estimated. The latter is able to detect additional patterns related to the effects of the covariates. Prices are regressed on wine color, sub-regional area of origin, the type of certification of origin, and on experts' evaluation. The analysis is based on data released by three major Italian wine guides: Gambero Rosso, l'Espresso, and AIS (Italian Sommelier Association). Results show that: (i) white and red wines follow two different price patterns; (ii) prices are correlated with experts' evaluation; (iii) the impact of the latter is higher when other quality clues, such as geographical indications, are less effective; (iv) the role of different quality clues varies at different price levels and it is different for red and white wines; overall, wines from the Lazio region are associated with poor to mediocre quality levels. This may explain the decline in reputation and in market share that these wines are experiencing after centuries of popularity.     

Quantile regression on the nonlinear relationship between land use and trip time

This study conceptually confirms and empirically tests the potential that the significance and magnitude of the compact land use–trip time relationship differ by the degree of compactness and trip time. Based on a quantile regression of about 25,000 commuters in Seoul, Korea, the empirical analysis suggests a significant level for each neighbourhood land use variable and a magnitude change within the level. Weekend trip and school densities are significant for shorter trip time commuters, population density is significant for longer trip time commuters, and pedestrian density is significant for all commuters. Wherever significant, the land use variables exert stronger effects as their values increase.     

Revisiting CO2 emissions convergence in G18 countries

This study revisits whether CO₂ emissions converge in G18 countries over the period of 1950–2013. To work on this empirical analysis, we employ a more powerful quantile unit root test with per capita CO₂ emissions. While conventional unit root tests fail to reject convergence in CO₂ emissions in these G18 countries, quantile unit root test results demonstrate CO₂ emissions converged in 5 of these G18 countries (i.e., Australia, Brazil, Canada, Germany, and India). Our empirical results have important policy implications for the governments of G18 countries to direct efficient and effective energy policies to reduce the CO₂ emissions.