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區域化變量非正態分布的穩健性

Stationarity for the non-normal distribution of regionalized variables

  • 摘要: 從區域化變量分布的穩健性角度,借鑒產品加工質量精度控制的理論,基于Johnson分布曲線族提出了一套非正態數據轉換方法,并設計了轉換流程.以SPSS和Surpac礦業軟件為工具,通過實際案例分析了傳統數據轉換方法和Johnson轉換方法的應用效果.實踐證明,采用上述方法轉化后的數據開展統計分析、變異函數模型的擬合及驗證、克立格估計等工作,更容易滿足穩健性要求,并能從本質上減小估計誤差,提高估計精度.

     

    Abstract: Based on Johnson distribution curves and the theory of product process quality accuracy control, a method to transform non-normal distribution data was proposed from the view of regionalized variable distribution, and the transformation flow was also designed. With SPSS and Surpac mining software as tools, the applied efficiency of traditional data and Johnson transform methods was analyzed through several cases. It is proved that by using the transformed data of the proposed method, the statistical analysis, fitting and validation of the variation function model, and Kriging estimation could meet the need of stationary, the estimation error can be minimized, and the precision of prediction can be improved.

     

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