Re: AI-GEOSTATS: mysterious kriging output

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• Hi Ruben, thanks so much for the references .... and especially the R routines .... i will look into it. This may really give some good answers to my data -
Message 1 of 2 , Mar 9, 2004
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Hi Ruben,

thanks so much for the references .... and especially the R
routines .... i will look into it. This may really give some good
answers to my data - once for all - i hope at least. I think we
neglect in majority of cases to verify if the data come from one or 2
(or more) distributions and just apply a transformation and do a
kriging .... it is just too easy that way ;-))

Again, thank you so much,

Monica

> Exploratory analysis of the frequency distribution of the data (i.e. the
> aggregated, non-spatial, frequency) could reveal the existence of two (or
> more) populations. To evaluate the evidence in favour of such an
> hypothesis, you could compare the hypothesis that the frequency
> distribution is formed by a mixture of two (or more) specified
> distributions versus the hypothesis that it is formed by only one. The
> general topic in statistics is called 'mixture distribution analysis' (not
> to be confused with 'mixture models'). Useful references are:
>
> Everitt & Hand, 1981, Mixture distribution analysis. Chapman & Hall
> Chen & Chen, 2001, Statistics and Probability Letters 52:125
> Hawkins et al., 2001, Computational Statistics & Data Analysis 38:15
> http://www.math.mcmaster.ca/peter/mix/mix.html
>
> Some robust regression methods, for example, are based on treating the
> data as coming from a mixture of two distributions, the main one, and a
> contaminating distribution.
>
> If you conclude that there are two (or more) distributions, then you can
> compute the maximum conditional probability that any given data point
> belong to any of the two (or more) distributions, and use this computation
> to classify data. After this exploratory analysis, you could treat the two
> (or more) populations differently, if there is evidence for a mixture, and
> maybe even perform separate geostatistical analyses on the separate
> populations.
>
> I used this general strategy in the analysis of a time series of an index
> of returns from investments in finantial markets. The strategy was
> proposed by Hamilton, 1994, Time Series Analysis, Ch. 22, Princeton U. P.
>
> Ruben

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