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Recent research has sought to develop a statistically based approach to setting environmental standards, prompted by Barnett and O'Hagan ( 1997 ) whose recommendations for a statistically verifiable ideal standard (SVIS) were endorsed by the Royal Commission on Environmental Pollution ( 1998 ). Many current environmental standards are set without due consideration of uncertainty and variation and are often based on poorly defined principles. In this article we propose an SVIS set on a population quantile where inferences about that quantile are achieved through best linear unbiased quantile estimation (BLUQE). We concentrate on estimation using small samples from the normal distribution with both parameters unknown, as is often the case in environmental problems. We investigate the efficiency of this estimator in comparison with a quantile estimator based upon the common sample estimators of mean and standard deviation, X̄ and S, respectively. From extensive simulation, we tabulate 5 per cent and 1 per cent critical values for the 0.95 and 0.99 BLUQE and develop an approximate significance testing procedure, which we demonstrate using river water quality data. We consider the difference in power between this approximate test and a coefficient of variation‐based approach appealing to properties of the non‐central t distribution. Finally, we examine ranked set sampling and compare best linear unbiased quantile estimation based on ranked set samples with that based on ordinary random samples, demonstrating impressive efficiency gains. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
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灌溉水经济价值是农业用水定价的重要基础。根据陕西关中地区农户调研数据,采用剩余价值法计算得到小麦、玉米和苹果灌溉水经济价值均值分别为0.66 元/m3、0.84 元/m3、3.17 元/m3。以该结果作为水价调整上限与现状水价比较,小麦和玉米的水价上调空间介于0.24~0.71元/m3,苹果的水价调整空间介于2.72~3.04 元/m3之间。使用分位数模型对影响因素的研究发现：（1）仅在灌溉水经济价值较低时,农户和家庭特征以及土地分散程度有显著影响;（2）在灌溉水经济价值较高时,增强农户节水意识以及加入用水者协会将能有效提升灌溉用水经济价值;（3）粮食转为经济作物、进行农业水价综合改革在所有分位点上均呈显著正向影响。本文可为研究区域农业用水分类定价及改善用水效率提供参考。 相似文献
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Maximum analysis consists of modeling the maximums of a data set by considering a specific distribution. Extreme value theory (EVT) shows that, for a sufficiently large block size, the maxima distribution is approximated by the generalized extreme value (GEV) distribution. Under EVT, it is important to observe the high quantiles of the distribution. In this sense, quantile regression techniques fit the data analysis of maxima by using the GEV distribution. In this context, this work presents the quantile regression extension for the GEV distribution. In addition, a time‐varying quantile regression model is presented, and the important properties of this approach are displayed. The parameter estimation of these new models is carried out under the Bayesian paradigm. The results of the temperature data and river quota application show the advantage of using this model, which allows us to estimate directly the quantiles as a function of the covariates. This shows which of them influences the occurrence of extreme temperature and the magnitude of this influence. 相似文献
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Wastewater treatment is one of critical issues faced by water utilities, and receives more and more attentions recently. The energy consumption modeling in biochemical wastewater treatment was investigated in the study via a general and robust approach based on Bayesian semi-parametric quantile regression. The dataset was derived from a municipal wastewater treatment plant, where the energy consumption of unit chemical oxygen demand (COD) reduction was the response variable of interest. Via the proposed approach, the comprehensive regression pictures of the energy consumption and truly influencing factors, i.e., the regression relationships at lower, median and higher energy consumption levels were characterized respectively. Meanwhile, the proposals for energy saving in different cases were also facilitated specifically. First, the lower level of energy consumption was closely associated with the temperature of influent wastewater, and the chroma-rich wastewater also showed helpful in the execution of energy saving. Second, at median energy consumption level, the COD-rich wastewater played a determinative role in the reduction of energy consumption, while the higher quality of treated water led to slightly energy intensive. Third, the higher level of energy consumption was most likely to be attributed to the relatively high temperature of wastewater and total nitrogen (TN)-rich wastewater, and both of the factors were preferably to be avoided to alleviate the burden of energy consumption. The study provided an efficient approach to controlling the energy consumption of wastewater treatment in the perspective of statistical regression modeling, and offered valuable suggestions for the future energy saving. 相似文献
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In environmental applications it is common for the extremes of a variable to be non‐stationary, varying systematically in space, time or with the values of covariates. Multi‐site datasets are common, and in such cases there is likely to be non‐negligible inter‐site dependence. We consider applications in which multi‐site data are used to infer the marginal behaviour of the extremes at individual sites, while adjusting for inter‐site dependence. For reasons of statistical efficiency, it is standard to model exceedances of a high threshold. Choosing an appropriate threshold can be problematic, particularly if the extremes are non‐stationary. We propose a method for setting a covariate‐dependent threshold using quantile regression. We consider how the quantile regression model and extreme value models fitted to threshold exceedances should be parameterized, in order that they are compatible. We adjust estimates of uncertainty for spatial dependence using methodology proposed recently. These methods are illustrated using time series of storm peak significant wave heights from 72 sites in the Gulf of Mexico. A simulation study illustrates the applicability of the proposed methodology more generally. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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采取多种空间分析的方法,对2002～2020年交通运输业碳排放强度的时空交互特征进行剖析,通过得到的时空跃迁类型与面板分位数模型进行嵌套来探究其跃迁机制,最后根据不同的跃迁机制引入地理探测器模型来考察影响交通运输业碳排放强度的不同因素之间的交互作用效应.结果表明：(1)中国30个省区的交通运输业碳排放强度整体呈波动下降态势,在空间上的聚集水平也相对稳定.(2)ESTDA的时空交互特征表明,西北地区和周边邻接空间单位的关系不稳定,变化和波动较大.而东部沿海城市等经济发达地区已经形成了成熟的交通运输网络,因此局部空间格局也相对稳定,但仍有部分地区存在时空竞争性.(3)交通运输业碳排放强度时空跃迁可分为4类驱动或制约模式（人口-经济-城镇化制约模式;人口-经济-城镇化-设施制约模式;技术-消费-产业驱动模式和技术-产业-规制驱动模式）.大部分省份受低分位制约和高分位驱动两种模式的影响,仅有少部分省份受高分位制约和低分位驱动的作用影响,且绝大多数属于西北或西南地区.(4)根据得出的交通运输业碳排放强度跃迁机制进一步引入地理探测器模型,注重多因子的协调发展,加强区域间协同治理. 相似文献
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Associations of pollution with expected rates of morbidity and mortality are discussed extensively in the literature, but associations between pollution and quantiles of these rates may change substantially. In this study, we compare the association of pollution and climate variables controlling for seasonality with the expectation and quantile of the hospitalization rate. The generalized linear model with the binomial negative distribution and the quantile regression are fitted to the daily number of hospitalizations of resident people older than 65 years in São Paulo City from 2006 to 2011. The daily average nitrogen oxide concentration presented the most significant association with the expected hospitalization rate and with the 90th percentile of this rate but no significant association with the median rate, controlling for seasonality and climate variables. The minimum temperature and relative humidity presented significant association with the expected hospitalization rate but no significant association with the 90th percentile. The effects may be very distinct for the average rate or high quantiles, which may affect planning the number of hospital beds mainly during the winter. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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为实现我国较大及以上生产安全事故(MWSA)数据的有效管理,减少事故发生及降低事故严重程度,基于2010—2022年国务院安委会挂牌督办的278起MWSA,建立通用的MWSA数据库,从事故发生时间、空间、行业、类型维度探究事故特征分布,并依据事故严重程度的综合量化指标,构建分位数回归模型全面识别事故严重程度的影响因素。结果表明:在时空分布上,6—9月的事故起数和死亡人数处于高峰,日照充足的白天(7:00—18:00)事故起数和死亡人数占比多达2/3,经济发达省/直辖市(京津江浙沪闽)事故较少;爆炸和车辆伤害为主要事故类型。在0.05的显著性水平下,事故类型、发生日期、季节、日照条件、天气、平均温度、企业员工规模、企业成立时长等8个因素分别在不同分位点处与事故严重程度显著相关。其中,天气、平均温度是低严重度事故中影响事故后果的重要因素,100人以下的企业员工规模因素增大了极端严重事故发生的可能性。 相似文献
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Chien-Chiang Lee Godwin Olasehinde-Williams Bright Akwasi Gyamfi 《Sustainable Development》2023,31(2):976-989
It is commonly argued in what is termed the degrowth strategy that economic growth cannot occur side by side with environmental protection. In this study, it is instead argued that the spread of green products through economic complexity and international trade are possible means of solving this problem. To this end, the individual and interactive environmental impacts of economic complexity and international green trade are examined in a panel of 24 European Union nations between 2000 and 2018. Panel quantile regressions (QRs) and Driscoll-Kraay fixed effect-OLS regressions are employed in analysing the relationships. The findings reveal that both green trade and economic complexity have beneficial individual effects on the environment. Their interaction effect further confirms that they have a complementary synergistic impact on the environment of the 24 EU countries. It thus implies that both green trade and economic complexity act better together than separately. Countries interested in achieving sustainable environment can do so by raising local productive capabilities, such that they are able to quickly transition into the production of technology-intensive, eco-friendly items. Alternatively, they can also explore the unique benefits provided by international trade in green products in cases where they do not have the ability to locally produce certain green goods. Better still, they can pursue both objectives simultaneously. 相似文献