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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