Quantification of variability and uncertainty using mixture distributions : evaluation of sample size, mixing weights, and separation between components

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      <subfield code="a">Quantification of variability and uncertainty using mixture distributions</subfield>
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      <subfield code="c">Junyu Zheng, H. Christopher Frey</subfield>
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      <subfield code="a">Probabilistic methods are being developed to quantitatively describe both variability and uncertainty. In this article the approach for using mixture  distributions and bootstrap simulation is illustrated with a case study  of an empirical data set. This article focuses on  mixture long-normal distributions with two components since a log- normal distribution describes random variability resulting from multiplicative processes and often well describes the  concentration of a chemical in the environment</subfield>
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      <subfield code="a">Frey, Christopher H.</subfield>
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      <subfield code="a">Risk analysis : an international journal</subfield>
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      <subfield code="g">nº 3, June 2004 ; p. 553-571</subfield>
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