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

 
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<title>Quantification of variability and uncertainty using mixture distributions</title>
<subTitle>: evaluation of sample size, mixing weights, and separation between components</subTitle>
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<title>Risk analysis : an international journal</title>
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<namePart>Zheng, Junyu</namePart>
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<namePart>Frey, Christopher H.</namePart>
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<dateIssued encoding="marc">2004</dateIssued>
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<abstract>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</abstract>
<note type="statement of responsibility">Junyu Zheng, H. Christopher Frey</note>
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<topic>Métodos estadísticos</topic>
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<topic>Matemáticas</topic>
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<subject authority="lcshac" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080616106">
<topic>Cálculo de probabilidades</topic>
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<subject authority="lcshac" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080597177">
<topic>Ingeniería ambiental</topic>
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<title>Risk analysis : an international journal</title>
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<publisher>New York and London</publisher>
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<identifier type="local">MAP20077000345</identifier>
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<text>nº 3, June 2004 ; p. 553-571</text>
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