分形理论及其在土壤空间变异研究中的应用

土壤具有不同程度的空间变异性,土壤空间变异研究对于土壤管理有重要意义.本文简要综述了分形理论及其在土壤空间变异研究中的应用,重点讨论了利用矩方法计算土壤属性分形维,多重分形分析土壤空间变异性及基于多重分形谱参数的土壤属性尺度转换.早期研究验证了分形理论在分析土壤空间变异中的有效性和应用潜力,国内外近期研究则报道了利用分形及多重分形理论分析土壤空间变异的最新进展.分形理论可以成为量化土壤属性空间变异性及尺度转换的重要工具.     

On the Online Detection of Monotonic Trends in Time Series

The online detection of a monotonic trend in a time series with a time‐varying mean is an important task in medical applications like intensive care monitoring, that is rendered difficult by autocorrelations. Statistical control charts designed for industrial processes are not adequate as they typically rely on a fixed target value, and many detection rules assume a trend to be linear or neglect autocorrelations. We report our experience with the online detection of slow monotonic trends. Our approach is based on a moving time window, and time‐varying autocorrelations are estimated online using parametric assumptions. The performance of versions of this approach is investigated in a simulation study. We find that shrinkage estimation of the time‐varying mean improves the results. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)