Logratio Statistics and the Extraction of Environmental,Signals from Grain-Size Data
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摘要: 沉积物粒度研究是沉积水动力环境研究的重要手段之一。由于闭合效应的影响，经典统计方法难以揭示粒度数据的真实特征。对数比统计分析是克服闭合效应的有效途径。本文介绍了波罗的海西部和南海北部的两个研究实例，在原始数据的经典统计分析不能揭示样品的自然分类的情况下，以粒度数据的对数比变换为基础的ＲＱ型主分量分析揭示出各沉积物类型之间的明显差异，而根据这种沉积物分类进行的沉积分区清晰地反映了沉积水动力环境的空间变化特征。Abstract: Grain-size distributions of sediments contain important information on sedimentary source, dynamics and environment. The correct use of statistical techniques to extract as much as possible useful signals from grain-size data is of crucial significance. When applying multivariate analysis to grain-size data, however, the auther encountered the problem of "closure",which may mask true patterns significantly. The logratio statistics is an effective way to avoid this problem. This paper presents two case studies respectively in the western Baltic Sea and northern South China Sea. While the classical statistics failed in representing the natural clustering of sediment samples, the RQ-mode principal components analysis based on logratio transforms of grain-size data made a clear separation among sediment classes. The sedimentary regionalization based on this classification successfully reflects the spacial variation of sedimetary hydredynamic environments in these areas.
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