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.     

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.     

Comparative analysis of discretization methods in Bayesian networks

A key step in implementing Bayesian networks (BNs) is the discretization of continuous variables. There are several mathematical methods for constructing discrete distributions, the implications of which on the resulting model has not been discussed in literature. Discretization invariably results in loss of information, and both the discretization method and the number of intervals determines the level of such loss. We designed an experiment to evaluate the impact of commonly used discretization methods and number of intervals on the developed BNs. The conditional probability tables, model predictions, and management recommendations were compared and shown to be different among models. However, none of the models did uniformly well in all comparison criteria. As we cannot justify using one discretization method against others, we recommend caution when discretization is used, and a verification process that includes evaluating alternative methods to ensure that the conclusions are not an artifact of the discretization approach.     

基于贝叶斯复合分位数回归的参数估计及应用

针对传统最小二乘估计易受异常点干扰及稳健性较差的问题,建立了基于复合分位数回归估计的数据拟合预测模型。为了克服复合分位数回归在估计参数时忽视了参数的不确定性,致使估算出的参数精度不够高的缺点,将贝叶斯分析法与复合分位数回归相结合,提高了参数的估算精度。实证分析表明贝叶斯复合分位数回归估计优于复合分位数回归估计,而复合分位数回归估计优于传统最小二乘估计,值得工程技术人员借鉴。     

HYPOTHESIS TESTING FOR ARCH MODELS: A MULTIPLE QUANTILE REGRESSIONS APPROACH

We propose a quantile regression‐based test to detect the presence of autoregressive conditional heteroscedasticity by combining distributional information across multiple quantiles. A chi‐square‐type test statistic based on the weighted average of distinct regression quantile estimators is formed. Unlike the widely used likelihood‐based tests, the proposed test does not make any distributional assumptions on the underlying errors. Monte Carlo simulation studies show that the proposed test outperforms the likelihood‐based tests in several aspects.