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Parametric and Bootstrap Estimations of Confidence Intervals for Analyte Concentrations of Composite Samples

GAO Zhi, HE Xi wen , LI Yi jun (Department of Chemistry, Nankai University, Tianjin, 300071, P.R.C.)  
Based on the initial analytical results of pig irons, Monte Carlo technique was used for the simulation of composite sampling. The confidence intervals of the concentration of Si, Mn, C, S, P in composite samples were studied with parametric and bootstrap methods, and the estimated results were compared. It shows that if the parent distribution complies with the Gaussian (or t distribution) discipline or if the composite sample contains a large number of increments, the estimated confidence intervals for two methods are in accordance with each other. However, if the parent distribution deviates greatly from the Gaussian distribution (or t distribution) and the composite sample contains a small number of increments, bootstrap method gives more reasonable confidence intervals than parametric method.
【Fund】: 国家自然科学基金! (编号 :2 95 75 2 0 0 )
【CateGory Index】: O651
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