Re: GEOSTATS: Variogram model selection
- Dear all.
Sorry it have took long time to post the summary
concerning my question.
The first question,
>We have found following three criteria in some papers.
> We read some books on geostatistics.
> In application to actual data in most books,
> it is not shown that why the semivariograms appeared in the analysis
> are selected.
> Does anyone have reference or comments ?
1. goodness of fit in variogram model fitting.
2. cross validation in kriging.
3. Akaike's Information Criterion with MLE.
In our analysis, criterion 1 has selected Gaussian model.
But the kriging surface with the fitted Gaussian model
has very strange feature.
The next question,
> I have one more question.In analysis with density of metal or something,
> If we assume a process is Gaussian,
> maximum likelihood (ML) estimator or
> restricted maximum likelihood (REML) estimator can be made
> for estimation of its covariance structure.
> I want to know another distributional assumptions on
> stochastic process which are often used in practice.
many data behave like log normal distribution.
So, in this case, the data are to be log transformed.
Another transformation for non-normal data is
to disjunctive kriging.
Thank you those who have responsed my question.
Dept. Math. Sci, Fac. Eng. Sci,
Osaka Univ., Toyonaka, Osaka 560, JAPAN
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