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矿床以其化验值、厚度、矿层顶、底面等等的一定连续性为特征。它们相对空间座标应服从随机模型。法国学派(Matheron,1963)在一次差分(d=1)数据的二阶平稳假设条件下,为了定量评价矿床储量和平均品位,提出了相当困难的术语——半变异函数(Semi—Varioyom)、克里金(Kriging)等等。本文介绍的是多数情况更适用、更有效和众所周知的时间域(空间)随机模型(ARIMA(p.d.g);是以Box和Jenkias,1970,1976,Anderson,1976为基础;马特隆模型(d=1)只是其中的一个特例。
The deposit is characterized by a certain continuity of its test value, thickness, top, bottom and so on. Their relative spatial coordinates should obey the stochastic model. The French School (Matheron, 1963) proposed a rather difficult term, Semi-Varioyom, for the purpose of quantitatively evaluating both reserve and average grade under the assumption of second-order stationary assumptions of a difference (d = 1) Kriging and many more. This article presents the more applicable, validated and well-known time domain (space) stochastic model (ARIMA (pdg); is based on Box and Jenkias, 1970, 1976, Anderson, 1976; 1) is just one of the special cases.