CHAPTER 2: The
Semi-Variogram
CONCLUSION
To summarise this chapter, we have seen how to calculate an experimental
semi-variogram in one and two dimensions, and how to relate this ‘practical’
semi-variogram to the ‘ideal’ models which exist. We have seen that, whilst
some deposits may follow fairly simple behaviour, many others require a fairly
complex mixture of models to describe the experimental semi-variogram. I have
briefly pointed out some problem areas such as strong trends, random phenomena
and proportional effect, and tried to indicate how these might be tackled.
There are those in authority who say that the fitting of a semi-variogram model
is out-moded and unnecessary. To counter this I should like to give an analogy
with ordinary statistics. If you take a limited number of samples from an
exceedingly large population and construct a histogram, are you prepared to
assume that that sample histogram
describes exactly the behaviour of the whole population? The process of
inference -- drawing conclusions about the population from a few samples --
demands the construction of some sort of model for the behaviour of the whole
deposit.