ESTIMATION OF DISTRIBUTIONAL PARAMETERS FOR CENSORED TRACE-LEVEL WATER-QUALITY DATA
ESTIMATION OF DISTRIBUTIONAL PARAMETERS FOR CENSORED TRACE-LEVEL WATER-QUALITY DATA
复制标题
截尾痕量水质数据分布参数的估计
DOI：
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发表时间：
1984
期刊：
影响因子：
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通讯作者：
D. Helsel
中科院分区：
文献类型：
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作者：
R. Gilliom;D. Helsel
在环境水中的许多金属和有机污染物的研究中经常遇到的困难是大部分水样浓度低于分析实验室确定的检测限。评估了几种仅使用未经审查的观察结果来估计此类审查数据集的分布参数的方法。它们的可靠性通过蒙特卡罗实验进行评估，其中从广泛的母体分布中生成小样本，并在不同级别进行审查。使用八种方法来估计平均值、标准差、中位数和四分位距。根据未经审查的观测值的分布制定了标准，用于确定任何特定数据集的最佳参数估计方法。在所有模拟条件下最小化四个分布参数的截尾样本估计误差的最稳健方法是对数概率回归方法。使用此方法，假设截尾观测值遵循对数正态分布的零至截尾水平部分，该对数正态分布是通过未截尾浓度观测值的对数与其 z 分数之间的最小二乘回归获得的。当在所有模拟条件下单独评估每个分布参数的方法性能时，对数概率回归方法的均值和标准差的误差仍然最小，但对数正态最大似然法的中位数和四分位数范围的误差最小。当在参数估计之前将数据集分类为反映其可能父分布的组时，估计方法的排名相似，但误差估计的准确性比未分类的方法显着提高。 6 个无花果，6 个标签。« 更少
A recurring difficulty encountered in investigations of many metals and organic contaminants in ambient waters is that a substantial portion of water-sample concentrations are below limits of detection established by analytical laboratories. Several methods were evaluated for estimating distributional parameters for such censored data sets using only uncensored observations. Their reliabilities were evaluated by a Monte Carlo experiment in which small samples were generated from a wide range of parent distributions and censored at varying levels. Eight methods were used to estimate the mean, standard deviation, median, and interquartile range. Criteria were developed, based on the distribution of uncensored observations, for determining the best-performing parameter estimation method for any particular data set. The most robust method for minimizing error in censored-sample estimates of the four distributional parameters over all simulation conditions was the log-probability regression method. With this method, censored observations are assumed to follow the zero-to-censoring level portion of a lognormal distribution obtained by a least-squares regression between logarithms of uncensored concentration observations and their z scores. When method performance was separately evaluated for each distributional parameter over all simulation conditions, the log-probability regression method still had the smallest errors for the mean and standard deviation, but the lognormalmore » maximum likelihood method had the smallest errors for the median and interquartile range. When data sets were classified prior to parameter estimation into groups reflecting their probable parent distributions, the ranking of estimation methods was similar, but the accuracy of error estimates was markedly improved over those without classification. 6 figs., 6 tabs.« less