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进口铁矿砷量特征的内核密度分析与Bootstrap代表值估计
Study on arsenic content by kernel density estimation and bootstrap method in imported iron ore
【摘要】 对进口铁矿中的砷量进行了总体统计分析,在数据统计分布特征研究基础上,使用内核密度估计对进口铁矿砷量进行数据多态性分析,使用boot-strap对原始数据样本值重复取样以获得稳健的砷量代表值估计及标准偏差,证明以bootstrap重新取样样本分布的均值与标准偏差作为有限单次样本代表值是合理、有效的。
【Abstract】 Content characteristic of arsenic in iron ores imported was investigated by statistical techniques.Based on data distribution,a brand-new robust statistics, kernel density estimation,coupled with bootstrap resampling method was introduced to acquire the representative value of arsenic content in imported iron ores.It is clearly demonstrates that this method shows a prior advantage to give a robust descriptions in explanation for central tendency and variation of data profiles.A bootstrap mean and interval were provided,and further discussion was hold in detail.
【Key words】 Ion ore; Arsenic; Representative value; Statistical description; Kernel density estimation; Bootstrap;
- 【文献出处】 分析试验室 ,Chinese Journal of Analysis Laboratory , 编辑部邮箱 ,2007年01期
- 【分类号】F752.61;F224
- 【被引频次】4
- 【下载频次】105